2518 Data Scientist Jobs - Page 40

Job Description Job Profile - Lead, Data Scientist We are looking for a passionate ML /AI Lead Data Scientist with demonstrated thought-leadership & proven ability to lead the development of analytics-focused products and utilizing cutting edge machine learning, natural language processing, and mathematical techniques to drive powerful business results. You will have the opportunity to work with a wide range of stakeholders and functional teams to help them discover insights hidden in data sets and enable stakeholders to improve business. AI ethics, fairness and secure development practices are also our focus areas. Responsibilities Partners with lines of business to understand business problems and translate them into identifiable machine learning problems which can be delivered as technical solutions and actionable recommendations across the organization Coordinate with business teams to monitor outcomes and refine/ improve the machine learning models Work across the spectrum of statistical modelling including supervised, unsupervised, & deep learning techniques to apply the right level of solution to the right problem Collaborate & share best practices with data and software engineers to enable consistent deployment of high-quality models that will scale across the company s ecosystem Own the code review process to ensure stringent coding guidelines are met by other data scientists & data engineers Mentor & lead Data Science engineers in choosing the right machine learning approach/ models & utilizing open source languages such as R, Python, etc. Lead data mining and collection procedures for all business use cases and guarantee data quality and integrity Utilize Data visualization tools to deliver insights to stakeholders and present technical solutions to non-technical audience in a simple and clear manner Track emerging developments w.r.t technology, tools, practices, etc in the open source, data science/machine learning/chatbot domain and leverage same for Schneider Electric Build frameworks leveraging APIs to industrialize AI models across the organization Adhere to stringent quality assurance and documentation standards using version control and code repositories (e.g., Git, GitHub, Markdown) Requirements and Skills You should have bachelor s or Master s degree in Computer Science, Statistics or Mathematics, Informatics, Information Systems or another quantitative field You should have experience in solving real life complex business problems using machine learning. Hands-on experience in deploying these machine learning solutions to production is mandatory. In depth understanding of NLP, LLM, Generative AI, RAG application development. In-depth understanding and modeling experience in supervised, unsupervised, reinforcement and deep learning models; hands-on knowledge of data wrangling, data cleaning/ preparation, dimensionality reduction is required Knowledge of vector algebra, statistical and probabilistic modelling is highly desirable Exploratory data analysis and hypothesis testing to identify ML opportunities is a plus Experience in major machine learning frameworks such as Pytorch, Scikit-Learn, Tensorflow, Pandas, SparkML etc. Fluency in programming skills such as Python, R, or other equivalent languages Familiarity with databases like MySQL, Oracle, SQL Server, NoSQL, etc. is desirable Experience working with Amazon SageMaker or Azure ML Studio for deployments is required Experience in data visualization software such as Tableau, ELK, etc is a plus Strong analytical and critical thinking skills. You should also have a business mindset, swift to identify risk situations and opportunities, and able to generate creative solutions to business problems Effective communication skills (written and verbal) to properly articulate complicated statistical models/ reports to management and other IT development partners About Us Schneider Electric creates connected technologies that reshape industries, transform cities and enrich lives. Our 144,000 employees thrive in more than 100 countries. From the simplest of switches to complex operational systems, our technology, software and services improve the way our customers manage and automate their operations. Help us deliver solutions that ensure Life Is On everywhere, for everyone and at every moment: Great people make Schneider Electric a great company. We seek out and reward people for putting the customer first, being disruptive to the status quo, embracing different perspectives, continuously learning, and acting like owners. We want our employees to reflect the diversity of the communities in which we operate. We welcome people as they are, creating an inclusive culture where all forms of diversity are seen as a real value for the company. We re looking for people with a passion for success on the job and beyond. Qualifications Responsibilities Partners with lines of business to understand business problems and translate them into identifiable machine learning problems which can be delivered as technical solutions and actionable recommendations across the organization Coordinate with business teams to monitor outcomes and refine/ improve the machine learning models Work across the spectrum of statistical modelling including supervised, unsupervised, & deep learning techniques to apply the right level of solution to the right problem Collaborate & share best practices with data and software engineers to enable consistent deployment of high-quality models that will scale across the company s ecosystem Own the code review process to ensure stringent coding guidelines are met by other data scientists & data engineers Mentor & lead Data Science engineers in choosing the right machine learning approach/ models & utilizing open source languages such as R, Python, etc. Lead data mining and collection procedures for all business use cases and guarantee data quality and integrity Utilize Data visualization tools to deliver insights to stakeholders and present technical solutions to non-technical audience in a simple and clear manner Track emerging developments w.r.t technology, tools, practices, etc in the open source, data science/machine learning/chatbot domain and leverage same for Schneider Electric Build frameworks leveraging APIs to industrialize AI models across the organization Adhere to stringent quality assurance and documentation standards using version control and code repositories (e.g., Git, GitHub, Markdown) Requirements and Skills You should have bachelor s or Master s degree in Computer Science, Statistics or Mathematics, Informatics, Information Systems or another quantitative field You should have 7+ years of experience in solving real life complex business problems using machine learning. Hands-on experience in deploying these machine learning solutions to production is mandatory. In depth understanding of NLP, LLM, Generative AI, RAG application development. In-depth understanding and modeling experience in supervised, unsupervised, reinforcement and deep learning models; hands-on knowledge of data wrangling, data cleaning/ preparation, dimensionality reduction is required Knowledge of vector algebra, statistical and probabilistic modelling is highly desirable Exploratory data analysis and hypothesis testing to identify ML opportunities is a plus Experience in major machine learning frameworks such as Pytorch, Scikit-Learn, Tensorflow, Pandas, SparkML etc. Fluency in programming skills such as Python, R, or other equivalent languages Familiarity with databases like MySQL, Oracle, SQL Server, NoSQL, etc. is desirable Experience working with Amazon SageMaker or Azure ML Studio for deployments is required Experience in data visualization software such as Tableau, ELK, etc is a plus Strong analytical and critical thinking skills. You should also have a business mindset, swift to identify risk situations and opportunities, and able to generate creative solutions to business problems Effective communication skills (written and verbal) to properly articulate complicated statistical models/ reports to management and other IT development partners Schedule: Full-time Req: 009G5J

Build cutting edge models using NLP, ML and AI Techniques for a variety of problems in a variety of domains. Work with engineering team to deploy models in production & validate the models. Expert level knowledge in Natural Language Processing, Information Extraction, Scrapping and Text Mining Algorithms, Tech Stacks. Strong familiarity with deep learning methods for text analytics. Expert level knowledge in Machine Learning algorithms (XGBoost, Linear and Logistic Regression, SVM, Random Forest, Bayesian Methods, Unsupervised Learning, Reinforcement Learning) is a must. Familiarity and experience of working on time series analysis on real world datasets. Familiarity with flask, fastapi, hug. Must be an expert python programmer. Demonstrated expertise via high quality publications and/or competitions/challenges. Ability to easily work with domain experts and passion to make a difference. Minimum B.E/B.Tech in computer science/ Electrical Engineering/ EXTC with a strong base in mathematics and statistics. Strong communication skills and team player. Ability to thrive in a startup environment. Problem solving attitude is a must. Desired Candidate Profile Data Scientist to join team and completely take care of Text Analytics on Qualitative Customer Feedback and Call Center complaints conversations via Email or Chat.

Being part of and contributing to a large, vibrant community Understanding problems and designing solutions for the P&C Insurance industry. Applying a variety of analytic methodologies including Predictive Modeling, Machine Learning, Forecasting, Network Analytics, Natural Language Processing, Computer Vision, Voice and Speech Analytics, and Generative AI to develop solutions to those business problems Working with a diverse set of extremely rich datasets such as 19 billion detailed records of insurance premiums collected and losses paid, or 90%+ of Insurance Claims in the US Seeing your work result in new products, product enhancements, consulting revenue, or internal process improvements on a regular basis Working with cutting-edge technology, and continuously developing new skills and capabilities. A degree in a quantitative field with relevant experience: Bachelors (3-5 years) or Masters (1-2 years), or PhD (0-2 years). Strong programming skills, particularly in R and Python. Extensive experience in one or more of the following skills is essential: Predictive Modeling, Entity Resolution, NLP, and Generative AI. Experience in any of the following skills is a plus: Big Data Platforms, Time-Series Forecasting, Graph Databases, Network Analytics, Neural Networks, Computer Vision, and ASR (Automated Speech Recognition). Familiarity with SQL or NoSQL (eg, Hadoop, HBase, MongoDB and/or Neo4j) databases. Domain knowledge in the insurance industry is an added advantage. Ability to solve problems analytically and creatively. Strong communication (written and oral) skills. The development and timely delivery of analytic solutions that meet business requirements around accuracy, sophistication, and interpretability. Develop analytic solutions using machine learning techniques including Predictive Modeling, Text Mining, Entity Resolution, Time-series Forecasting, Network Analytics, Computer Vision, Automated Speech Recognition, and Generative AI. Ensure that solutions meet business requirements around accuracy, sophistication, and interpretability. Ensure that solution is delivered in a timely manner. The incorporation of technical innovations and new developments in relevant analytic fields Keep abreast of technical innovations and new developments in relevant analytic fields The development of analytic interns that you are responsible for Identify training opportunities and project opportunities that can help develop the analytic interns you are responsible for The sharing of important methodologies, advances, and best practices from your work among the whole analytic community Help organize these forums for developing Verisk s analytic community Share important methodologies, advances, and best practices from your work among the whole analytic community via these forums. Success Criteria: Measurable contribution to products and processes in terms of new products developed, enhanced products, direct revenue supported, cost savings etc Positive feedback on the support received from business partners Advancement of analytic interns that you are responsible for Positive feedback from analytic interns that you are responsible for Positive feedback from team members and leaders of the Verisk analytic community

We are looking for a Staff Data Scientist to join our Silicon Verification Data Science team. In this role, you will use advanced data science, AI/ML techniques to drive efficiency, automation, and innovation in Silicon Design Verification. You will work closely with hardware engineers, verification teams, and software developers to optimize verification workflows, improve coverage, and accelerate time-to-market for cutting-edge semiconductor products. As a Staff Engineer/ Data Scientist at Micron, you will Develop AI and Data Science based solutions to build state-of-the-art solutions for silicon design verification and firmware validation. Identify patterns, anomalies, and inefficiencies in silicon design verification processes and develop solutions to address these gaps. Automate data pipelines and develop tools to support regression analysis, bug triaging, and root cause analysis. Partner with cross-functional teams to integrate data-driven solutions into EDA tools and verification frameworks. Drive technical innovation and culture within the team by participating in generating IP and inspiring team to innovate. Participate in end-to-end project scoping and stakeholder discussions to determine technical merit of the idea, vale proposition and resource requirements. Interact with subject matter experts to define scope, identify risks, deploy scalable solutions & lead multiple projects execution Continuously learn as we'll as mentor team on recent progress on semiconductor and AI/ML domain. Key requirements: Education: masters or PhD in Computer Science, Electrical Engineering, or a related field. Experience: 8+ years in data science and machine learning with at least 2 years in semiconductor verification environment Technical Skills In-depth understanding of Statistics, classical ML and deep learning, and the mathematics and formulation behind these algorithms. we'll versed with text processing, various methodologies in data embedding, NLP techniques and recent advancements in GenAI and LLMs. Hands-on experience with optimization and reinforcement learning based algorithms. Solid understanding of data engineering pipeline for deployment and MLOps. Proficiency in programming languages such as Python, R, and SQL. Experience with machine learning frameworks (eg, TensorFlow, PyTorch) and data visualization tools (eg, Tableau, Power BI). Strong understanding of digital design and verification concepts (eg, RTL, UVM, coverage metrics, simulation). Experience with EDA tools (eg, Synopsys VCS, Cadence Xcelium, Mentor Questa) and verification flows is a great plus. Preferred Qualifications: Knowledge of hardware description languages (Verilog/SystemVerilog). Experience with CI/CD pipelines and MLOps practices. Patents or publications in relevant fields.

Responsible for conducting in-depth analysis of complex datasets, deploying predictive models, applying optimization techniques, designing decision support systems, analyzing experiments, collaborating with cross-functional teams, staying abreast of advancements, and assessing the impact of data-driven decisions. Grade - T2 What your main responsibilities are: 1. Conduct in-depth analysis of complex data sets to uncover actionable insights and trends. 2. Develop and deploy predictive models to forecast business outcomes and support decision-making processes. 3. Apply optimization techniques to improve business processes and resource allocation. 4. Design and implement decision support systems that enable stakeholders to make data-driven decisions. 5. Design and analyze experiments to evaluate the effectiveness of business strategies and interventions. 6. Collaborate with cross-functional teams and stakeholders to understand business requirements and priorities. 7. Stay abreast of advancements in data science, machine learning, and decision science to enhance analytical capabilities. 8. Assess the impact of data-driven decisions on key business metrics and outcomes and iterate on models and strategies accordingly. What we are looking for Education: Bachelors degree or equivalent in Computer Science, MIS, Mathematics, Statistics, or similar discipline. Masters degree or PhD is preferred. Relevant work experience in decision science based on the following number of years: Standard I: Two (2) years Standard II: Three (3) years Senior I: Four (4) years Senior II: Five (5) years Knowledge, Skills and Abilities Fluency in English Analytical Skills Accuracy & Attention to Detail Numerical Skills Planning & Organizing Skills Presentation Skills Statistical and Mathematical Knowledge Data Modeling and Visualization Skills Programming Skills

Job Title: Data Scientist AI/ML, Generative AI & Databricks Experience: 2-3 Years; 3-5+ Years Employment Type: Full-Time Job Description: We are seeking a highly skilled and experienced Senior Data Scientist who thrives at the intersection of Machine Learning, Generative AI, and Cloud-native MLOps. The ideal candidate will have hands-on experience building end-to-end AI/ML models, working with Large Language Models (LLMs), deploying solutions at scale, and leveraging the full potential of the Databricks ecosystem. Responsibilities: Design, build, and deploy scalable machine learning and AI models using Databricks, from ideation to production. Develop and fine-tune Generative AI and LLM-based solutions for use cases such as summarization, text generation, and synthetic data generation. Drive MLOps best practices using tools like MLflow, Delta Lake, and Unity Catalog for model versioning, reproducibility, and governance. Collaborate with product managers, data engineers, and other data scientists to deliver impactful solutions to business problems. Optimize model performance, conduct error analysis, and ensure efficient cloud resource utilization in Azure or AWS environments. Lead technical discussions, code reviews, and mentor junior data scientists within the team. Stay abreast of the latest research and trends in AI/ML and proactively apply them to real-world use cases. Communicate technical findings clearly to both technical and non-technical stakeholders. Qualifications: Bachelors or Master’s degree in Computer Science, Data Science, Engineering, or a related field. 3+ years of experience in applied data science, AI, and machine learning. Proven expertise in developing ML models from scratch, including preprocessing, feature engineering, and model tuning. Hands-on experience with LLMs and Generative AI (e.g., GPT, LLaMA, Falcon, etc.) and fine-tuning domain-specific models. Advanced programming skills in Python, with experience in relevant ML libraries (e.g., scikit-learn, PyTorch, TensorFlow). Deep familiarity with the Databricks platform: Delta Lake, Agent Bricks, Unity Catalog, MLflow, Mosaic AI, and integration with cloud ecosystems (Azure/AWS). Solid understanding of MLOps principles, CI/CD pipelines, and production-level deployments. Excellent communication and interpersonal skills with the ability to simplify complex concepts.

Join our Team About This Opportunity The complexity of running and optimizing the next generation of wireless networks, such as 5G with distributed edge compute, will require Machine Learning (ML) and Artificial Intelligence (AI) technologies Ericsson is setting up an AI Accelerator Hub in India to fast-track our strategy execution, using Machine Intelligence (MI) to drive thought leadership, automate, and transform Ericssons offerings and operations We collaborate with academia and industry to develop state-of-the-art solutions that simplify and automate processes, creating new value through data insights What You Will Do As a Senior Data Scientist, you will apply your knowledge of data science and ML tools backed with strong programming skills to solve real-world problems Responsibilities: Lead AI/ML features/capabilities in product/business areas Define business metrics of success for AI/ML projects and translate them into model metrics Lead end-to-end development and deployment of Generative AI solutions for enterprise use cases Design and implement architectures for vector search, embedding models, and RAG systems Fine-tune and evaluate large language models (LLMs) for domain-specific tasks Collaborate with stakeholders to translate vague problems into concrete Generative AI use cases Develop and deploy generative AI solutions using AWS services such as SageMaker, Bedrock, and other AWS AI tools Provide technical expertise and guidance on implementing GenAI models and best practices within the AWS ecosystem Develop secure, scalable, and production-grade AI pipelines Ensure ethical and responsible AI practices Mentor junior team members in GenAI frameworks and best practices Stay current with research and industry trends in Generative AI and apply cutting-edge techniques Contribute to internal AI governance, tooling frameworks, and reusable components Work with large datasets including petabytes of 4G/5G networks and IoT data Propose/select/test predictive models and other ML systems Define visualization and dashboarding requirements with business stakeholders Build proof-of-concepts for business opportunities using AI/ML Lead functional and technical analysis to define AI/ML-driven business opportunities Work with multiple data sources and apply the right feature engineering to AI models Lead studies and creative usage of new/existing data sources What You Will Bring Bachelors/Masters/Ph D in Computer Science, Data Science, AI, ML, Electrical Engineering, or related disciplines from reputed institutes 3+ years of applied ML/AI production-level experience Strong programming skills (R/Python) Proven ability to lead AI/ML projects end-to-end Strong grounding in mathematics, probability, and statistics Hands-on experience with data analysis, visualization techniques, and ML frameworks (Python, R, H2O, Keras, TensorFlow, Spark ML) Experience with semi-structured/unstructured data for AI/ML models Strong understanding of building AI models using Deep Neural Networks Experience with Big Data technologies (Hadoop, Cassandra) Ability to source and combine data from multiple sources for ML models Preferred Qualifications: Good communication skills in English Certifying MI MOOCs, a plus Domain knowledge in Telecommunication/IoT, a plus Experience with data visualization and dashboard creation, a plus Knowledge of Cognitive models, a plus Experience in partnering and collaborative co-creation in a global matrix organization Why join Ericsson At Ericsson, you?ll have an outstanding opportunity The chance to use your skills and imagination to push the boundaries of what?s possible To build solutions never seen before to some of the worlds toughest problems You?ll be challenged, but you wont be alone You?ll be joining a team of diverse innovators, all driven to go beyond the status quo to craft what comes next What happens once you apply Click Here to find all you need to know about what our typical hiring process looks like Encouraging a diverse and inclusive organization is core to our values at Ericsson, that's why we champion it in everything we do We truly believe that by collaborating with people with different experiences we drive innovation, which is essential for our future growth We encourage people from all backgrounds to apply and realize their full potential as part of our Ericsson team Ericsson is proud to be an Equal Opportunity Employer learn more Primary country and city: India (IN) || Bangalore Req ID: 766481

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.