2411 Data Scientist Jobs - Page 36

Minimum qualifications: Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field 5 years of work experience using analytics to solve product or business problems, coding (e g , Python, R, SQL), querying databases or statistical analysis, or 3 years of work experience with a PhD degree Preferred qualifications: 8 years of work experience using analytics to solve product or business problems, coding (e g , Python, R, SQL), querying databases or statistical analysis, or 6 years of work experience with a PhD degree Experience articulating and translating business questions and using statistical techniques to arrive at an answer using available data About The Job At Google, data drives all of our decision-making Quantitative Analysts work all across the organization to help shape Google's business and technical strategies by processing, analyzing and interpreting huge data sets Using analytical excellence and statistical methods, you mine through data to identify opportunities for Google and our clients to operate more efficiently, from enhancing advertising efficacy to network infrastructure optimization to studying user behavior As an analyst, you do more than just crunch the numbers You work with Engineers, Product Managers, Sales Associates and Marketing teams to adjust Google's practices according to your findings Identifying the problem is only half the job; you also figure out the solution The team's mission is to protect Android users from abusive apps, including malware, content abuse, impersonation, and behavioral abuse As a Data Scientist on the App Safety Engineering (ASE) team, you will work with multiple stakeholders across product, engineering, and operation teams to conduct data research, build methodologies into production systems to drive ASE key decisions and development You will be responsible for translating data into recommendations and implementing process improvements Responsibilities Work with datasets, solve non-routine analysis problems, and apply quantitative methods as needed Conduct analysis that includes data gathering and requirements specification, processing, analysis, model development and evaluation, as well as written and verbal delivery of results to business partners Collaborate with stakeholders in Product Management, Engineering, and Operation teams to define questions, objectives, and metrics, identify and implement quantitative methods to answer those questions Develop, own, and evolve methodologies and frameworks providing a source of truth measures for the organization Establish comprehensive understanding of the production systems, advocate for changes where needed for product development, and build data driven solutions to faciliate the efficacy improvement Google is proud to be an equal opportunity workplace and is an affirmative action employer We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status We also consider qualified applicants regardless of criminal histories, consistent with legal requirements See also Google's EEO Policy and EEO is the Law If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form

Minimum qualifications: Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, a related quantitative field, or equivalent practical experience 5 years of work experience with analysis applications (e g , extracting insights, performing statistical analysis, or solving business problems), and coding (e g , Python, R, SQL) (or 2 years work experience with a Master's degree) Preferred qualifications: Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field 5 years of work experience with analysis applications (e g , extracting insights, performing statistical analysis, or solving business problems), and coding (e g , Python, R, SQL) About The Job Help serve Google's worldwide user base of more than a billion people Data Scientists provide quantitative support, market understanding and a strategic perspective to our partners throughout the organization As a data-loving member of the team, you serve as an analytics expert for your partners, using numbers to help them make better decisions You will weave stories with meaningful insight from data You'll make critical recommendations for your fellow Googlers in Engineering and Product Management You relish tallying up the numbers one minute and communicating your findings to a team leader the next Google One is a subscription to Google that delivers expanded storage, premium features, and AI-powered experiences across Google products to members The team partners with teams across Google to deliver valuable experiences to users that drive engagement for business growth Google Photos is a photo sharing and storage service developed by Google Photos is one of the most sought after products at Google and is looking for both client-side (web and mobile), with server-side (search, storage, serving) and machine intelligence (learning, computer vision) Software Engineers We are dedicated to making Google experiences centered around the user Responsibilities Partner with Product Management, Engineering, and more in Analytics to understand the profile of Google One business, use data to evaluate how business is evolving and drive decisions based on insights Identify business problems and come up with analytical solutions that improve product and user experience Google is proud to be an equal opportunity workplace and is an affirmative action employer We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status We also consider qualified applicants regardless of criminal histories, consistent with legal requirements See also Google's EEO Policy and EEO is the Law If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form

B. Tech / B.E. from a Tier-1 Institution (IITs, IISc, IIITs, BITS, NITs or similar institutions), preferably in Computer Science, IT, Electronics Engineering, Electrical Engineering, Mathematics or any other related field. Minimum 2+ years of hands-on experience in machine learning, deep learning, or computer vision roles. Strong expertise in deep learning frameworks such as PyTorch, TensorFlow, and Keras. In-depth knowledge of CNNs, Transformers, Siamese networks, contrastive learning, and embedding space analysis. Proficient in Python and experienced with largescale data processing tools like Spark, Dask, or Hadoop. Prior experience working with biometric, or image datasets (face, iris, fingerprint) is desirable. • Strong understanding of data cleaning, clustering (e.g., DBSCAN, K-Means), anomaly detection, and unsupervised learning. Knowledge of privacy-preserving techniques such as federated learning, differential privacy & homomorphic encryption is a plus. Job Profile Design and develop state-of-the-art deep learning models for biometric recognition (facial, fingerprint, iris) and fraud detection using convolutional neural networks (CNNs), transformers, and hybrid architectures. Lead the design of end-to-end AI pipelines: data ingestion, pre-processing, model training, evaluation, and deployment in production environments. Conduct thorough error analysis A/B testing, and performance evaluations to identify weaknesses and improve recognition accuracy and system efficiency. Architect scalable data pipelines for image and biometric signal cleaning, feature extraction, clustering, and deduplication at the national scale. Collaborate with domain experts, biometric vendors, and legal/policy teams to ensure technological solutions are interpretable, robust, and policy compliant. Monitor system drift, adversarial threats, and fraud patterns in biometric usage across the Aadhaar ecosystem. Publish internal technical reports and participate in peer reviewed research where appropriate. Mentor and guide junior data scientists and ML engineers in best practices. What We Offer Unique opportunity to work on the largest biometric identity system in the world. Access to UIDAIs unparalleled scale of identity data and secure research environments. Competitive compensation and benefits tailored for top-tier AI talent in the public sector. A mission-driven organization with direct impact on national scale governance, security, and inclusion

Company Description Derangula Consulting Inc. offers business intelligence, IT consultancy & support, and staffing services tailored to meet your business needs. Our team of experts is committed to helping you maximize the benefits of our services and support your business growth. We are seeking a skilled and motivated Data Scientist or Data Engineer with strong proficiency in Python and machine learning to join our growing data team. The ideal candidate will work on designing, building, and deploying scalable data and machine learning pipelines to support decision-making, product development, and strategic initiatives. Key Responsibilities: Design, develop, and prediction analysis with BI solutions. Build, train, and deploy machine learning models to solve prediction. Analyze large datasets to extract actionable insights and support business goals. Implement best practices for data quality, governance, and version control. Required Qualifications: Bachelor's or Master’s degree in Computer Science, Data Science, Engineering, or a related field. Strong proficiency in Python and related libraries (Pandas, NumPy, Scikit-learn, etc.). Hands-on experience with machine learning algorithms and model deployment. Solid knowledge of SQL and relational databases. Preferred Qualifications: Experience with deep learning frameworks (e.g., TensorFlow, PyTorch). Exposure to data warehousing solutions (e.g., Snowflake, BigQuery). 1.BI knowledge is must 2.Having any BI tool exp (Qlik, Tableau) If you’re passionate about turning historical data into actionable insights and have a track record of delivering reliable forecasts, we’d love to hear from you Feel free to call us -9390571086 Mail-derangulamahesh61@gmail.com

Building and maintaining systems for extracting, pre- processing and modelling for different data streams, as well as integrating data across different sources. Expertise in visualizations and data analysis. Creating predictive and prescriptive models that could have a positive impact on the business. Integrating data engineering and modelling algorithms/techniques and solutions into the backend systems Develop model monitoring infrastructure for periodic monitoring and upgradation of data science strategies and models Building & implementing state-of-the-art deep learning models. Working with various stakeholders to identify and capitalize on opportunities to leverage data to drive business solutions. R Programming / Python Scripting / SQL; Experience in Finance, R-Studio/Shiny. Experience 5 - 7 Years . Industry IT Software - Application Programming / Maintenance Qualification B.E Key Skills Data Analyst R Programming Python R Programmer

Job Description: Key Responsibilities: Design and develop machine learning and deep learning systems using frameworks like TensorFlow, PyTorch, and Scikit-learn. Implement real-time systems for forecasting, optimization, and personalized recommendations. Research and apply advanced AI/ML techniques, including Generative AI models (e.g., GPT, LLaMA) and NLP architectures. Lead end-to-end machine learning projects, from problem framing to deployment and monitoring. Manage model lifecycle activities, including training, testing, retraining, and fine-tuning for optimal performance. Collaborate with analytics teams, practice leads, subject matter experts, and customer teams to understand business objectives and technical requirements. Conduct statistical analysis to address business challenges and drive innovation in AI/ML applications. Deploy machine learning applications on cloud platforms (e.g., GCP, Azure, AWS) and ensure seamless integration with existing systems. Monitor system performance, address data drift, and ensure scalability and adaptability to evolving requirements. Qualifications: Minimum 7+ years for Principal Data Scientist roles (3+ years for Data Scientist roles) with proven expertise in AI/ML, particularly in Generative AI, NLP, and computer vision. Proficient in Python, Java, and R. Strong expertise in TensorFlow, PyTorch, Scikit-learn, Django, Flask, Numpy, and Pandas. Comprehensive knowledge of data structures, SQL, multi-threading, and APIs (RESTful, OData). Hands-on experience with Tableau and Power BI for data visualization. Strong understanding of statistics, probability, algorithms, and optimization techniques. Experience deploying ML applications on GCP, Azure, or AWS. Familiarity with ERP/SAP integration, post-production support, and lifecycle management of ML systems. Industry experience in retail, telecom, or supply chain optimization is a plus. Exceptional problem-solving skills, strong leadership capabilities, and excellent communication skills.

Position Name: Data Scientist/Lead Data Scientist Job Details: We are seeking a highly motivated and enthusiastic Junior Data Scientist with 5-10 years of experience to join our data science team. This role offers an exciting opportunity to contribute to both traditional Machine Learning projects for our commercial IoT platform and cutting-edge Generative AI initiatives. Experience 5-10 years of hands-on experience with machine learning Exposure to Generative AI concepts and techniques, such as Large Language Models (LLMs), RAG Architecture Experience in manufacturing and with an IoT platform is preferable Role and Responsibilities: Key Objectives Machine Learning (ML): Assist in the development and implementation of machine learning models using frameworks such as TensorFlow, PyTorch, or scikit-learn. Help with Python development to integrate models with the overall application Monitor and evaluate model performance using appropriate metrics and techniques. Generative AI: Build Gen AI-based tools for various business use cases by fine-tuning and adapting pre-trained generative models Support the exploration and experimentation with Generative AI models Research & Learning: Stay up-to-date with the latest advancements and help with POCs Proactively research and propose new techniques and tools to improve our data science capabilities. Collaboration and Communication: Work closely with cross-functional teams, including product managers, engineers, and business stakeholders, to understand requirements and deliver impactful solutions. Communicate findings, model performance, and technical concepts to both technical and non-technical audiences. Technical Competencies Programming: Proficiency in Python, with experience in libraries like numpy, pandas, and matplotlib for data manipulation and visualization. ML Frameworks: Experience with TensorFlow, PyTorch, or scikit-learn. Cloud & Deployment: Basic understanding of cloud platforms such as Databricks, Google Cloud Platform (GCP), or Microsoft Azure for model deployment. Data Processing & Evaluation: Knowledge of data preprocessing, feature engineering, and evaluation metrics such as accuracy, F1-score, and RMSE.

Educational Bachelor of Engineering Service Line AI & Automation Service Line Responsibilities Technical skills ProgrammingPython, R, SQL ML algorithms Statistical ML algorithms Deep Neural Network architectures Model ensembling Generative AI models ML for Responsible AI AI domains - NLP, speech, computer vision, structured data Learning patterns – supervised, unsupervised, reinforcement learning Tools for data analysis, auto ML, model deployment & scaling, model fine tuning Knowledge of different Model fine tuning approaches for Large models Knowledge of datasets, pre-built models available in open community and 3rd party providers Knowledge of software development & architectures Knowledge of hyperscalers & their AI capabilities – Azure, AWS, GCP Knowledge of Model Quantization and Pruning Past experience playing a Data Scientist role Technical and Professional : Technical skills ProgrammingPython, R, SQL ML algorithms Statistical ML algorithms Deep Neural Network architectures Model ensembling Generative AI models ML for Responsible AI AI domains - NLP, speech, computer vision, structured data Learning patterns – supervised, unsupervised, reinforcement learning Tools for data analysis, auto ML, model deployment & scaling, model fine tuning Knowledge of different Model fine tuning approaches for Large models Knowledge of datasets, pre-built models available in open community and 3rd party providers Knowledge of software development & architectures Knowledge of hyperscalers & their AI capabilities – Azure, AWS, GCP Knowledge of Model Quantization and Pruning Past experience playing a Data Scientist role Preferred Skills: Technology-Machine learning-data science Technology-Machine Learning-Python Technology-Machine Learning-Generative AI

Educational Bachelor of Engineering Service Line Data & Analytics Unit Responsibilities Preferred Proficiency with statistical analysis tools (e.g., SAS, SPSS, R & Python) Hands on experience in Statistical Techniques & Deep Learning such as Decision Tree, Segmentation, Logistic and Multiple Regression, and others Experience of Forecasting, Campaign Management andCustomer Segmentation is desirable Strong Excel, Access and PowerPoint skills Familiarity with database query tools (SQL) Basic understanding of data warehouse architecture Understanding of various Analytical Tools, Platform & Frameworks. Technical and Professional : Data science . machine learning Good to have PySpark/Databricks Preferred Skills: Technology-Data Science-Machine Learning

Develop, test and support future-ready data solutions for customers across industry verticals. Develop, test, and support end-to-end batch and near real-time data flows/pipelines. Demonstrate understanding of data architectures, modern data platforms, big data, analytics, cloud platforms, data governance and information management and associated technologies. Communicates risks and ensures understanding of these risks. Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Graduate with a minimum of 6+ years of related experience required. Experience in modelling and business system designs. Good hands-on experience on DataStage, Cloud-based ETL Services. Have great expertise in writing TSQL code. Well-versed with data warehouse schemas and OLAP techniques. Preferred technical and professional experience Ability to manage and make decisions about competing priorities and resources. Ability to delegate where appropriate. Must be a strong team player/leader. Ability to lead Data transformation projects with multiple junior data engineers. Strong oral written and interpersonal skills for interacting throughout all levels of the organization. Ability to communicate complex business problems and technical solutions.

Develop, test and support future-ready data solutions for customers across industry verticals. Develop, test, and support end-to-end batch and near real-time data flows/pipelines. Demonstrate understanding of data architectures, modern data platforms, big data, analytics, cloud platforms, data governance and information management and associated technologies. Communicates risks and ensures understanding of these risks. Graduate with a minimum of 5+ years of related experience required. Experience in modelling and business system designs. Good hands-on experience on DataStage, Cloud-based ETL Services. Have great expertise in writing TSQL code. Well-versed with data warehouse schemas and OLAP techniques. Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Ability to manage and make decisions about competing priorities and resources. Ability to delegate where appropriate. Must be a strong team player/leader. Preferred technical and professional experience Ability to lead Data transformation projects with multiple junior data engineers. Strong oral written and interpersonal skills for interacting throughout all levels of the organization. Ability to communicate complex business problems and technical solutions.

Work with broader team to build, analyze and improve the AI solutions. You will also work with our software developers in consuming different enterprise applications Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Resource should have 5-7 years of experience. Sound knowledge of Python and should know how to use the ML related services. Proficient in Python with focus on Data Analytics Packages. Strategy Analyse large, complex data sets and provide actionable insights to inform business decisions. Strategy Design and implementing data models that help in identifying patterns and trends. Collaboration Work with data engineers to optimize and maintain data pipelines. Perform quantitative analyses that translate data into actionable insights and provide analytical, data-driven decision-making. Identify and recommend process improvements to enhance the efficiency of the data platform. Develop and maintain data models, algorithms, and statistical models Preferred technical and professional experience Experience with conversation analytics. Experience with cloud technologies Experience with data exploration tools such as Tableu

Role Overview: As a Data Scientist within IBM's Chief Analytics Office, you will support AI-driven projects across the enterprise. You will apply your technical skills in AI, machine learning, and data analytics to assist in implementing data-driven solutions that align with business goals. This role involves working with team members to translate data insights into actionable recommendations. Key Responsibilities: Technical Execution and Leadership: Develop and deploy AI models and data analytics solutions. Support the implementation and optimization of AI-driven strategies per business stakeholder requirements. Help refine data-driven methodologies for transformation projects. Data Science and AI: Design and implement machine learning solutions and statistical models, from problem formulation through deployment, to analyze complex datasets and generate actionable insights. Learn and utilize cloud platforms to ensure the scalability of AI solutions. Leverage reusable assets and apply IBM standards for data science and development. Project Support: Lead and contribute to various stages of AI and data science projects, from data exploration to model development. Monitor project timelines and help resolve technical challenges. Design and implement measurement frameworks to benchmark AI solutions, quantifying business impact through KPIs. Collaboration: Ensure alignment to stakeholders’ strategic direction and tactical needs. Work with data engineers, software developers, and other team members to integrate AI solutions into existing systems. Contribute technical expertise to cross-functional teams. Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Experience: 2-4 yearsof experience in data science, AI, or analytics with a focus on implementing data-driven solutions Experience with data cleaning, data analysis, A/B testing, and data visualization Experience with AI technologies through coursework or projects Technical Skills: Proficiency in SQL and Python for performing data analysis and developing machine learning models Knowledge of common machine learning algorithms and frameworkslinear regression, decision trees, random forests, gradient boosting (e.g., XGBoost, LightGBM), neural networks, and deep learning frameworks such as TensorFlow and PyTorch Experience with cloud-based platforms and data processing frameworks Understanding of large language models (LLMs) Familiarity with IBM’s watsonx product suite Familiarity with object-oriented programming Analytical Skills: Strong problem-solving abilities and eagerness to learn Ability to work with datasets and derive insights Other : Good communication skills, with the ability to explain technical concepts clearly. Enthusiasm for learning and applying new technologies Strong project management skills, with the ability to balance multiple initiatives, prioritize tasks effectively, and meet deadlines in a fast-paced environment Successful completion of Coding Assessment Preferred technical and professional experience Education: Bachelor’s or Master’s in Computer Science, Data Science, Statistics, or a related field is required; an advanced degree strongly preferred Advanced degree strongly preferred. * Good communication skills, with the ability to explain technical concepts clearly * Enthusiasm for learning and applying new technologies * Strong project management skills, with the ability to balance multiple initiatives, prioritize tasks effectively, and meet deadlines in a fast-paced environment * Successful completion of Coding Assessment

As an Associate Data Scientist at IBM, you will work to solve business problems using leading edge and open-source tools such as Python, R, and TensorFlow, combined with IBM tools and our AI application suites. You will prepare, analyze, and understand data to deliver insight, predict emerging trends, and provide recommendations to stakeholders. In your role, you may be responsible for Implementing and validating predictive and prescriptive models and creating and maintaining statistical models with a focus on big data & incorporating machine learning. techniques in your projects Writing programs to cleanse and integrate data in an efficient and reusable manner Working in an Agile, collaborative environment, partnering with other scientists, engineers, consultants and database administrators of all backgrounds and disciplines to bring analytical rigor and statistical methods to the challenges of predicting behaviors Communicating with internal and external clients to understand and define business needs and appropriate modelling techniques to provide analytical solutions. Evaluating modelling results and communicating the results to technical and non-technical audiences Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Proof of Concept (POC) DevelopmentDevelop POCs to validate and showcase the feasibility and effectiveness of the proposed AI solutions. Collaborate with development teams to implement and iterate on POCs, ensuring alignment with customer requirements and expectations. Help in showcasing the ability of Gen AI code assistant to refactor/rewrite and document code from one language to another, particularly COBOL to JAVA through rapid prototypes/ PoC Document solution architectures, design decisions, implementation details, and lessons learned. Create technical documentation, white papers, and best practice guides Preferred technical and professional experience Strong programming skills, with proficiency in Python and experience with AI frameworks such as TensorFlow, PyTorch, Keras or Hugging Face. Understanding in the usage of libraries such as SciKit Learn, Pandas, Matplotlib, etc. Familiarity with cloud platforms Experience and working knowledge in COBOL & JAVA would be preferred

Role Overview: As a Data Scientist within IBM's Chief Analytics Office, you will support AI-driven projects across the enterprise. You will apply your technical skills in AI, machine learning, and data analytics to assist in implementing data-driven solutions that align with business goals. This role involves working with team members to translate data insights into actionable recommendations. Key Responsibilities: Technical Execution and Leadership: Develop and deploy AI models and data analytics solutions. Support the implementation and optimization of AI-driven strategies per business stakeholder requirements. Help refine data-driven methodologies for transformation projects. Data Science and AI: Design and implement machine learning solutions and statistical models, from problem formulation through deployment, to analyze complex datasets and generate actionable insights. Learn and utilize cloud platforms to ensure the scalability of AI solutions. Leverage reusable assets and apply IBM standards for data science and development. Project Support: Lead and contribute to various stages of AI and data science projects, from data exploration to model development. Monitor project timelines and help resolve technical challenges. Design and implement measurement frameworks to benchmark AI solutions, quantifying business impact through KPIs. Collaboration: Ensure alignment to stakeholders’ strategic direction and tactical needs. Work with data engineers, software developers, and other team members to integrate AI solutions into existing systems. Contribute technical expertise to cross-functional teams. Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Experience: 5+ yearsof experience in data science, AI, or analytics with a focus on implementing data-driven solutions Experience with data cleaning, data analysis, A/B testing, and data visualization Experience with AI technologies through coursework or projects Technical Skills: Proficiency in SQL and Python for performing data analysis and developing machine learning models Knowledge of common machine learning algorithms and frameworkslinear regression, decision trees, random forests, gradient boosting (e.g., XGBoost, LightGBM), neural networks, and deep learning frameworks such as TensorFlow and PyTorch Experience with cloud-based platforms and data processing frameworks Understanding of large language models (LLMs) Familiarity with IBM’s watsonx product suite Familiarity with object-oriented programming Analytical Skills: Strong problem-solving abilities and eagerness to learn Ability to work with datasets and derive insights Other : Good communication skills, with the ability to explain technical concepts clearly. Enthusiasm for learning and applying new technologies Strong project management skills, with the ability to balance multiple initiatives, prioritize tasks effectively, and meet deadlines in a fast-paced environment Successful completion of Coding Assessment Preferred technical and professional experience . Education: Bachelor’s or Master’s in Computer Science, Data Science, Statistics, or a related field is required; an advanced degree strongly preferred Advanced degree strongly preferred

Introduction: A Career at HARMAN Digital Transformation Solutions (DTS) We’re a global, multi-disciplinary team that’s putting the innovative power of technology to work and transforming tomorrow. At HARMAN DTS, you solve challenges by creating innovative solutions. Combine the physical and digital, making technology a more dynamic force to solve challenges and serve humanity’s needs Work at the convergence of cross channel UX, cloud, insightful data, IoT and mobility Empower companies to create new digital business models, enter new markets, and improve customer experiences What You Will Do End to end machine learning lifecycle management on Sagemaker Model training & tracking using MLFLow Model Monitoring Sagemaker Pipelines building Experience in using Sagemaker ground truth for optimised collection of annotated data (Plus). Cost and performance optimization What You Need To Be Successful Experience working in cross-functional teams and collaborating effectively with different stakeholders. Strong problem-solving and analytical skills. Excellent communication skills to document and present technical concepts clearly. What Makes You Eligible Bachelor’s or master’s degree in computer science, Artificial Intelligence, or a related field. 5-10 years relevant and Proven experience in developing and deploying generative AI models and agents in a professional setting. What We Offer Flexible work environment, allowing for full-time remote work globally for positions that can be performed outside a HARMAN or customer location Access to employee discounts on world-class Harman and Samsung products (JBL, HARMAN Kardon, AKG, etc.) Extensive training opportunities through our own HARMAN University Competitive wellness benefits Tuition reimbursement “Be Brilliant” employee recognition and rewards program An inclusive and diverse work environment that fosters and encourages professional and personal development You Belong Here HARMAN is committed to making every employee feel welcomed, valued, and empowered. No matter what role you play, we encourage you to share your ideas, voice your distinct perspective, and bring your whole self with you – all within a support-minded culture that celebrates what makes each of us unique. We also recognize that learning is a lifelong pursuit and want you to flourish. We proudly offer added opportunities for training, development, and continuing education, further empowering you to live the career you want. About HARMAN: Where Innovation Unleashes Next-Level Technology Ever since the 1920s, we’ve been amplifying the sense of sound. Today, that legacy endures, with integrated technology platforms that make the world smarter, safer, and more connected. Across automotive, lifestyle, and digital transformation solutions, we create innovative technologies that turn ordinary moments into extraordinary experiences. Our renowned automotive and lifestyle solutions can be found everywhere, from the music we play in our cars and homes to venues that feature today’s most sought-after performers, while our digital transformation solutions serve humanity by addressing the world’s ever-evolving needs and demands. Marketing our award-winning portfolio under 16 iconic brands, such as JBL, Mark Levinson, and Revel, we set ourselves apart by exceeding the highest engineering and design standards for our customers, our partners and each other. If you’re ready to innovate and do work that makes a lasting impact, join our talent community today! HARMAN is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or Protected Veterans status. HARMAN offers a great work environment, challenging career opportunities, professional training, and competitive compensation. (www.harman.com)

Job Description – Data Scientist Company: Tata Digital Private Limited Tata Digital is a future-ready company focused on building consumer-centric, high-engagement digital products. Our flagship offering, Tata Neu , is a super-app that integrates various consumer services, including groceries, fashion, electronics, travel, financial services, and more, into a seamless experience. As a wholly owned subsidiary of Tata Sons Private Limited , we are committed to driving digital transformation at scale. Role Details Role Title: Data Scientist / Machine Learning Engineer Function: Data Science Location: Bangalore Experience: 3-5 Y About the Role: We are looking for an experienced Data Scientist / Machine Learning Engineer to join our team and help drive innovation in search, recommendation, and ads. You will be responsible for designing, building, and optimizing ML models that enhance user experience and business outcomes at scale. If you have a strong background in developing scalable ML solutions within a product-driven company, we want to hear from you. Key Responsibilities: Develop and optimize ML models for search ranking, recommendations, and ad targeting to improve engagement and monetization. Design, implement, and deploy large-scale ML pipelines in production environments. Experiment with and improve deep learning, NLP, for personalization and relevance. Conduct A/B testing and data-driven evaluations to measure the impact of ML models. Optimize infrastructure and data processing for high-scale real-time and batch ML systems. Stay up to date with advancements in ML, AI, and big data technologies and apply them to business problems. Minimum Qualifications: 3+ years of experience in Data Science / Machine Learning Engineering, with a focus on search, recommendation systems, or advertising. Strong programming skills in Python, Scala, or Java with experience in ML frameworks like TensorFlow, PyTorch, or Scikit-learn . Experience with big data technologies (e.g., Spark, Hadoop, Kafka) and distributed computing. Proficiency in SQL and NoSQL databases for large-scale data processing. Hands-on experience in deploying ML models in production at scale (MLOps, CI/CD for ML). Strong understanding of ranking models, deep learning, NLP, and reinforcement learning. Preferred Qualifications: Familiarity with vector search, embeddings, and retrieval-based models. Strong problem-solving skills and ability to work in a fast-paced environment Experience with cloud platforms like AWS, GCP, or Azure . If you’re passionate about building intelligent, scalable, and high-impact ML solutions, apply now! Learn more about Tata Digital: Tata Neu Tata Digital Newsroom LinkedIn YouTube

Design and lead the development of various artificial intelligence initiatives to help improve health and wellness of patients Work with the business leaders and customers to understand their pain-points and build large-scale solutions for them. Define technical architecture to productize Innovaccers machine-learning algorithms and take them to market with partnerships with different organizations Proven ability to break down complex business problems into machine learning problems and design solution workflows. Work with our data platform and applications team to help them successfully integrate the data science capability or algorithms in their product/workflows. Work with development teams to build tools for repeatable data tasks that will accelerate and automate development cycle. Stay updated on advancements in AI/ML technologies and apply them to enhance existing systems.

Role & responsibilities Responsibilities: JD: Data Scientist Responsibilities: Leverage strong ML model experience in complex data environments to achieve business objectives in innovative and efficient ways. Utilize a solid background in mathematics and statistics to inform model development and evaluation. Design, architect, and develop robust machine learning solutions, with a focus on integrating Large Language Models (LLMs) where applicable. Collaborate effectively within Agile Scrum teams, contributing to iterative development and continuous improvement. Document business processes, workflows, and requirements clearly and comprehensively. Engage in close collaboration with various domains within the organization to ensure alignment and understanding of business needs. Participate in collaborative conceptualization sessions to brainstorm and refine project ideas. Mandatory Skills: Proficiency in Python, Machine Learning, REST API, and SQL. Experience with data processing, cleansing, and verification to ensure data integrity for analysis. Conduct data quality checks and exploratory analyses to inform model development. Demonstrated programming skills in relevant languages, particularly Python and API development. Build end-to-end machine learning models, including data structures and transformation processes. Strong understanding of statistical modeling techniques (e.g., Regression, Clustering, Decision Trees, Logistic Regression). Familiarity with machine learning algorithms (e.g., KNN, Random Forests, Ensemble Methods, Bayesian/Markov Networks). Knowledge of data mining concepts and experience with data visualization tools and dashboards. Preferred Skills: Experience with Large Language Models (LLMs) such as GPT, BERT, or similar architectures. Understanding of natural language processing (NLP) techniques and their applications in business contexts. Familiarity with advanced research topics, including deep learning, kernel methods, spectral methods, and forecasting. Ability to integrate end-to-end ML solutions into product suites and business functions, with a focus on LLM applications. Design technical frameworks based on various use cases, particularly those involving text data and language understanding. Identify opportunities to automate analytical processes, data extraction, and flow processes, especially in the context of LLMs. Propose hypotheses and design experiments to address specific problems, leveraging LLM capabilities where relevant. Additional Responsibilities: Stay updated with the latest advancements in machine learning and natural language processing, particularly in the context of LLMs. Mentor junior team members on best practices in machine learning and LLM implementation. Contribute to the development of best practices and standards for machine learning and LLM projects within the organization. Profile Required:) JD: Data Scientist Responsibilities: Leverage strong ML model experience in complex data environments to achieve business objectives in innovative and efficient ways. Utilize a solid background in mathematics and statistics to inform model development and evaluation. Design, architect, and develop robust machine learning solutions, with a focus on integrating Large Language Models (LLMs) where applicable. Collaborate effectively within Agile Scrum teams, contributing to iterative development and continuous improvement. Document business processes, workflows, and requirements clearly and comprehensively. Engage in close collaboration with various domains within the organization to ensure alignment and understanding of business needs. Participate in collaborative conceptualization sessions to brainstorm and refine project ideas. Specific Context Additional Responsibilities: Stay updated with the latest advancements in machine learning and natural language processing, particularly in the context of LLMs. Mentor junior team members on best practices in machine learning and LLM implementation. Contribute to the development of best practices and standards for machine learning and LLM projects within the organization. Environment At Socit Gnrale, we are convinced that people are drivers of change, and that the world of tomorrow will be shaped by all their initiatives, from the smallest to the most ambitious. Whether youre joining us for a period of months, years or your entire career, together we can have a positive impact on the future. Creating, daring, innovating, and taking action are part of our DNA. If you too want to be directly involved, grow in a stimulating and caring environment, feel useful on a daily basis and develop or strengthen your expertise, you will feel right at home with us! Still hesitating? You should know that our employees can dedicate several days per year to solidarity actions during their working hours, including sponsoring people struggling with their orientation or professional integration, participating in the financial education of young apprentices, and sharing their skills with charities. There are many ways to get involved. We are committed to support accelerating our Group’s ESG strategy by implementing ESG principles in all our activities and policies. They are translated in our business activity (ESG assessment, reporting, project management or IT activities), our work environment and in our responsible practices for environment protection. Preferred candidate profile

Role & responsibilities We are seeking an experienced Senior Data Scientist with a strong background in traditional Machine Learning (ML), AI, and expertise in Azure Fabric to work in the Finance Department of a Bank. The ideal candidate will play a key role in applying advanced analytics to drive business insights, improve processes, and enhance decision-making in the banking sector. The candidate should be proficient in ML models and AI technologies with a focus on real-world banking applications and have hands-on experience with Azure Fabric. Mandatory Skills Proven experience in traditional Machine Learning (ML) and Artificial Intelligence (AI). Strong experience in Azure Fabric and its integration with various banking systems. Expertise in Data Science methodologies, predictive modelling, and statistical analysis. Solid understanding of the Finance domain with a focus on banking processes and challenges. Hands-on experience with cloud platforms (Azure). Experience in the banking or financial services industry. Key Responsibilities Design and implement Machine Learning (ML) and Traditional Artificial Intelligence (AI) models to solve complex business problems in the finance sector. Work closely with business stakeholders to understand requirements and translate them into data-driven solutions. Develop and deploy ML models on Azure Fabric, ensuring their scalability and efficiency. Analyze large datasets to identify trends, patterns, and insights to support decision-making. Collaborate with cross-functional teams to integrate AI/ML solutions into business processes and banking systems. Maintain and optimize deployed models and ensure their continuous performance. Keep up to date with industry trends, technologies, and best practices in AI and ML, specifically within the finance industry. Qualifications Education: Bachelors/Masters degree in Computer Science, Data Science, Engineering, or related field. Certifications: Relevant certifications in Data Science, Azure AI, or Machine Learning is a plus. Technical Skills Expertise in Machine Learning (ML) algorithms (Supervised and Unsupervised). Strong experience with Azure Fabric and related Azure cloud services. Familiarity with Python and data science libraries (Pandas, Scikit-learn, TensorFlow). Experience in AI and Deep Learning models, including neural networks. . Compensation & Benefits Competitive salary and annual performance-based bonuses Comprehensive health and optional Parental insurance. Optional Retirement savings plans and tax savings plans. Work-Life Balance: Flexible work hours KRA (Key Result Areas) Timely and effective delivery of ML/AI models that solve complex business problems. Continuous improvement and optimization of deployed models. High-quality insights and data-driven solutions delivered for business stakeholders. Client satisfaction with AI/ML solutions implemented within the banking domain. KPI (Key Performance Indicators) Number of successful ML/AI models deployed and their performance post-deployment. Model accuracy and predictive capability (based on business goals). Client feedback on AI-driven solutions. Completion time for delivering actionable data-driven insights. Team collaboration and mentoring effectiveness with junior data scientists Preferred candidate profile Soft Skills Excellent problem-solving and analytical skills. Strong communication skills, with the ability to present complex data insights clearly to non-technical stakeholders. Ability to work effectively in a collaborative, cross-functional environment. Strong attention to detail and ability to manage multiple tasks simultaneously. A passion for continuous learning and staying updated on new technologies. Good to Have Familiarity with DevOps practices for ML/AI model deployment. Knowledge of cloud-native architecture and containerization (Docker, Kubernetes). Familiarity with Deep Learning and Natural Language Processing (NLP) techniques. Familiarity with SQL and NoSQL databases. Experience with version control systems (Git, GitHub, etc.). Work Experience 8-12 years of experience in Data Science, with hands-on experience in ML, AI, and working within the finance or banking industry. Proven track record of designing and deploying machine learning models and working with Azure Fabric. Experience with client-facing roles and delivering solutions that impact business decision-making

Roles & responsibilities Serve as the AI & data strategist , discovering and onboarding new data sources and shaping end-to-end pipelines that span traditional analytics, machine learning (ML), deep learning (DL), natural-language processing (NLP), generative AI (Gen AI), and agentic AI . Partner with engineering to design, build, and harden production-grade data and AI products (e.g., RAG search, LLM-powered assistants, anomaly-detection services). Run analytical experiments classification, forecasting, LLM fine-tuning, prompt-engineering A/B tests to solve business problems across multiple domains. Collect, clean, and enrich large structured, semi-structured, and unstructured datasets (text, image, audio, sensor, graph). Design, train, and validate classical ML models, DL architectures (CNN, RNN, Transformers), and instruction-tuned LLMs ; measure drift and conduct error analysis to drive iterative improvement. Implement retrieval-augmented generation and agentic task-planning pipelines that combine vector search, function calling, and tool invocation. Document findings, publish reusable components, and mentor junior data scientists and ML engineers. Qualifications Experience Proven experience in delivering data-driven solutions, with demonstrable depth in at least two of: ML, DL, NLP, GenAI, agentic AI. Hands-on proficiency in Python (pandas, NumPy, scikit-learn), DL frameworks (TensorFlow or PyTorch), and LLM / GenAI toolkits (Hugging Face Transformers, LangChain/LangGraph, Google ADK). Proven track record in feature engineering, pattern recognition, predictive modeling, and LLM fine-tuning / evaluation . Experience optimizing GPU / TPU workloads and scaling distributed training or inference. Familiarity with vector databases (FAISS, Chroma, Pinecone) and distributed data systems (Spark, BigQuery, Snowflake). sibilities Preferred candidate profile

InnoWave is looking for a talented and analytical Data Scientist with 2–3 years of experience to join our dynamic team. The ideal candidate will have a strong foundation in data analysis, machine learning, and statistical modeling, and will be passionate about transforming data into actionable insights to support decision-making across projects. Responsibilities Analyze large and complex datasets to identify trends, patterns, and actionable insights Design, develop, and implement machine learning models to solve business problems Collaborate with cross-functional teams to understand business objectives and data needs Present analytical findings and model results clearly to both technical and non-technical stakeholders Create data visualizations and dashboards to communicate insights effectively Develop and maintain robust data pipelines and data wrangling scripts Monitor model performance and continuously improve algorithms Stay updated with the latest advancements in data science and machine learning Required Skills & Qualifications Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, Data Science, or a related field 2–3 years of hands-on experience in a data science or analytics role Strong proficiency in Python or R for data analysis and modeling Experience with machine learning libraries such as Scikit-learn, TensorFlow, or PyTorch Solid understanding of statistical techniques and their real-world applications Experience with SQL and working with relational databases Familiarity with data visualization tools such as Power BI, Tableau, or matplotlib/seaborn Excellent problem-solving skills and attention to detail Strong communication and collaboration skills

The Role and Responsibilities We have open positions ranging from Data Scientist to Director, providing talented and motivated professionals with excellent career and growth opportunities. We seek individuals with relevant prior experience in quantitatively intense areas to join our team. Youll be working with varied and diverse teams to deliver unique and unprecedented solutions across all industries. In the data scientist track, you will be primarily responsible for managing and delivering analytics projects and helping teams design analytics solutions and models that consistently drive scalable high-quality solutions. Your responsibilities will include Working alongside Oliver Wyman consulting teams and partners, engaging directly with global clients to understand their business challenges Exploring large-scale data and crafting models to answer core business problems Working with partners and principals to shape proposals that showcase our data science and analytics capabilities Explaining, refining, and crafting model insights and architecture to guide stakeholders through the journey of model building Advocating best practices in modelling and code hygiene Leading the development of proprietary statistical techniques, ML algorithms, assets, and analytical tools on varied projects Travelling to clients locations across the globe, when required, understanding their problems, and delivering appropriate solutions in collaboration with them Keeping up with emerging state-of-the-art modelling and data science techniques in your domain Your Attributes, Experience & Qualifications Bachelor's or Masters degree in a quantitative discipline from a top academic program (Data Science, Mathematics, Statistics, Computer Science, Informatics, and Engineering) Prior experience in data science, machine learning, and analytics Passion for problem-solving through big-data and analytics Pragmatic and methodical approach to solutions and delivery with a focus on impact Independent worker with the ability to manage workload and meet deadlines in a fast-paced environment Impactful presentation skills that succinctly and efficiently convey findings, results, strategic insights, and implications Excellent verbal and written communication skills and complete command of English Willingness to travel Collaborative team player Respect for confidentiality Technical Background Proficiency in modern programming languages (Python is mandatory; SQL, R, SAS desired) and machine learning frameworks (e.g., Scikit-Learn, TensorFlow, Keras/Theano, Torch, Caffe, MxNet) Prior experience in designing and deploying large-scale technical solutions leveraging analytics Solid foundational knowledge of the mathematical and statistical principles of data science Familiarity with cloud storage, handling big data, and computational frameworks Valued but not required: Compelling side projects or contributions to the Open-Source community Experience presenting at data science conferences and connections within the data science community Interest/background in Financial Services in particular, as well as other sectors where Oliver Wyman has a strategic presence

The Company PayPal has been revolutionizing commerce globally for more than 25 years. Creating innovative experiences that make moving money, selling, and shopping simple, personalized, and secure, PayPal empowers consumers and businesses in approximately 200 markets to join and thrive in the global economy. We operate a global, two-sided network at scale that connects hundreds of millions of merchants and consumers. We help merchants and consumers connect, transact, and complete payments, whether they are online or in person. PayPal is more than a connection to third-party payment networks. We provide proprietary payment solutions accepted by merchants that enable the completion of payments on our platform on behalf of our customers. We offer our customers the flexibility to use their accounts to purchase and receive payments for goods and services, as well as the ability to transfer and withdraw funds. We enable consumers to exchange funds more safely with merchants using a variety of funding sources, which may include a bank account, a PayPal or Venmo account balance, PayPal and Venmo branded credit products, a credit card, a debit card, certain cryptocurrencies, or other stored value products such as gift cards, and eligible credit card rewards. Our PayPal, Venmo, and Xoom products also make it safer and simpler for friends and family to transfer funds to each other. We offer merchants an end-to-end payments solution that provides authorization and settlement capabilities, as well as instant access to funds and payouts. We also help merchants connect with their customers, process exchanges and returns, and manage risk. We enable consumers to engage in cross-border shopping and merchants to extend their global reach while reducing the complexity and friction involved in enabling cross-border trade. Our beliefs are the foundation for how we conduct business every day. We live each day guided by our core values of Inclusion, Innovation, Collaboration, and Wellness. Together, our values ensure that we work together as one global team with our customers at the center of everything we do – and they push us to ensure we take care of ourselves, each other, and our communities. Job Description Summary: What you need to know about the role: In this role, you will lead a workstream solutions for complex, ambiguous and high-visibility business challenges. You will set and execute on a vision that reflects your deep analytical expertise. You will be a thought partner to Marketing leadership teams. Meet our team: Our Marketing Analytics transformation is in full swing. We embarked on a path of transforming and building a world class Marketing Analytics Org recently. Our team helps to power PayPal’s high growth Marketing organization by delivering actionable insights and business intelligence to Consumer Marketing Org for our 200+ million customers. Job Description: Your way to impact: You will partner with these teams to understand the insights they require to manage and grow their business and leverage cross-functional teams to develop and land solutions that meet their needs at scale. You are deeply curious and persistent in gaining knowledge about our products and go-to-market strategy. You will have exposure and visibility to PayPal Sales, Product, Finance & Market Insights teams, as you work with them to create a holistic solution to Marketing problems. We are a team of entrepreneurial, enthusiastic, and client-focused members. Your day to day: The successful candidate will be responsible for providing data-driven insights including but not limited to Business casing, Deep dives, Modelling, Campaign Performance readouts and optimisation. The candidate will also be responsible for delivering accurate, action driving recommendations to drive business performance and investment optimisation Manage multiple analytical projects at a time, in a fast-paced, intense, and results-oriented environment Influence stakeholders to make business decisions in alignment with global measurement approaches What do you need to bring: Degree in Statistics, Mathematics, Applied Mathematics, Computer Science, Operations Research, Engineering, Economics 2+ years of experience in analytics, data science or management consulting or equivalent analytical and project management experience Hands on experience of Python, SQL & BigQuery Accomplished Contributor, with experience managing high-performing Data Scientists and Quantitative Analysts Experience working within and driving strategy for large, global, complex organizations across multiple stakeholders and teams Exceptional problem-solving skills, with strong ability to drive towards action and impact Experience in managing analytics projects from inception to delivery, including developing structured solutions Experience with visualizations, dashboards, and reports Experience with data modelling, machine learning algorithms, and data science techniques. Experience explaining technical concepts and analysis implications to varied audiences and translating business objectives into analyses We know the confidence gap and imposter syndrome can get in the way of meeting spectacular candidates. Please don't hesitate to apply. For the majority of employees, PayPal's balanced hybrid work model offers 3 days in the office for effective in-person collaboration and 2 days at your choice of either the PayPal office or your home workspace, ensuring that you equally have the benefits and conveniences of both locations. Our Benefits: At PayPal, we’re committed to building an equitable and inclusive global economy. And we can’t do this without our most important asset—you. That’s why we offer benefits to help you thrive in every stage of life. We champion your financial, physical, and mental health by offering valuable benefits and resources to help you care for the whole you. We have great benefits including a flexible work environment, employee shares options, health and life insurance and more. To learn more about our benefits please visit https://www.paypalbenefits.com Who We Are: To learn more about our culture and community visit https://about.pypl.com/who-we-are/default.aspx Commitment to Diversity and Inclusion PayPal provides equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, pregnancy, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state, or local law. In addition, PayPal will provide reasonable accommodations for qualified individuals with disabilities. If you are unable to submit an application because of incompatible assistive technology or a disability, please contact us at paypalglobaltalentacquisition@paypal.com. Belonging at PayPal: Our employees are central to advancing our mission, and we strive to create an environment where everyone can do their best work with a sense of purpose and belonging. Belonging at PayPal means creating a workplace with a sense of acceptance and security where all employees feel included and valued. We are proud to have a diverse workforce reflective of the merchants, consumers, and communities that we serve, and we continue to take tangible actions to cultivate inclusivity and belonging at PayPal. Any general requests for consideration of your skills, please Join our Talent Community. We know the confidence gap and imposter syndrome can get in the way of meeting spectacular candidates. Please don’t hesitate to apply. REQ ID R0127500

The Opportunity: Works independently under close supervision, provide analysis, insight, and recommendations by synthesizing information for various product categories and geographies by using competitive analyses, analytical modeling, and leveraging knowledge of the product portfolio and customer programs. Manage pricing process for the sales team including assessing, approving, and loading all pricing requests. Review, research, and analyze pricing to make recommendations on price enhancements, SKU rationalization and margin opportunities. Process quotation requests for stock standard items and special order (customer specific) items. THE OPPORTUNITY: As a Data Scientist, you will leverage advanced statistical methods and machine learning techniques to analyze complex datasets, generate insights, and solve business problems. You will be responsible for developing and deploying ML models, performing deep-dive analyses, and collaborating with stakeholders to ensure the data strategy aligns with business objectives. WHAT WE'RE LOOKING FOR: The ideal candidate will be responsible for Collect, clean, and analyze large datasets to generate insights and recommendations. Develop and implement machine learning models to solve business problems. Maintain ML pipeline and fix production issues in stipulated time. Work on model maintenance and improvise model performance when necessary. Conduct hypothesis testing and statistical analyses to understand data trends. Communicate findings to non-technical stakeholders through reports and visualizations. Collaborate with engineers, product teams, and business stakeholders to translate business goals into data-driven solutions. CERTIFICATIONS (Good to have): ML/AI certifications Cloud certifications – like AWS, Azure, GCP etc. Databricks or Snowflake certification. EXPERIENCE: Bachelor’s or master’s degree in a quantitative field such as Data Science, Statistics, Computer Science, or Engineering. 2+ years of experience in working with a product development company as a ML/AI engineer. 2+ years of experience and proficiency in programming languages such as Python, Pyspark, Java. Strong hands-on experience in SQL or data manipulation/query language. 2+ years of experience with machine learning libraries (e.g., Scikit-learn, TensorFlow, PyTorch). Good knowledge on NLP, transformers, LLM and generative AI. Strong analytical skills and proficiency in statistical analysis and data visualization. Good communication and comprehension skills to explain ML algorithms to stakeholders in a non-technical manner. Good Team player and ability to work in cross-functional teams. HOW YOU WILL THRIVE AND CREATE AN IMPACT: With your analytical mindset and critical thinking, you will have the opportunity to participate in project development activities and suggest data driven and AI based solutions, which will be the foundation of the success of the project. With you proficient coding skills, you will have the opportunity to develop robust ML pipelines which will be modular, scalable and re-usable. You will have the opportunity to work with great minds who focusses on delivering quality products. Disclaimer: The above statements are intended to describe the general nature and level of work being performed by employees assigned to this classification. They are not intended to be construed as an exhaustive list of all responsibilities, duties and skills required of employees assigned to this position. Avantor is proud to be an equal opportunity employer. Why Avantor? Dare to go further in your career. Join our global team of 14,000+ associates whose passion for discovery and determination to overcome challenges relentlessly advances life-changing science. The work we do changes people's lives for the better. It brings new patient treatments and therapies to market, giving a cancer survivor the chance to walk his daughter down the aisle. It enables medical devices that help a little boy hear his mom's voice for the first time. Outcomes such as these create unlimited opportunities for you to contribute your talents, learn new skills and grow your career at Avantor. We are committed to helping you on this journey through our diverse, equitable and inclusive culture which includes learning experiences to support your career growth and success. At Avantor, dare to go further and see how the impact of your contributions set science in motion to create a better world. Apply today! EEO Statement: We are an Equal Employment/Affirmative Action employer and VEVRAA Federal Contractor. We do not discriminate in hiring on the basis of sex, gender identity, sexual orientation, race, color, religious creed, national origin, physical or mental disability, protected Veteran status, or any other characteristic protected by federal, state/province, or local law. If you need a reasonable accommodation for any part of the employment process, please contact us by email at recruiting@avantorsciences.com and let us know the nature of your request and your contact information. Requests for accommodation will be considered on a case-by-case basis. Please note that only inquiries concerning a request for reasonable accommodation will be responded to from this email address. 3rd party non-solicitation policy: By submitting candidates without having been formally assigned on and contracted for a specific job requisition by Avantor, or by failing to comply with the Avantor recruitment process, you forfeit any fee on the submitted candidates, regardless of your usual terms and conditions. Avantor works with a preferred supplier list and will take the initiative to engage with recruitment agencies based on its needs and will not be accepting any form of solicitation