1637 Predictive Modeling Jobs - Page 50

Key Responsibilities: Provide strategic guidance on AI adoption, ethics, and governance within the organization. Advise on AI-driven business models, innovation strategies, and regulatory compliance. Evaluate AI research, development, and deployment strategies to ensure ethical and sustainable growth. Mentor and collaborate with internal teams on best practices in AI, data science, and machine learning. Assess AI risks, biases, and challenges, providing solutions for responsible AI implementation.

Key Responsibilities: Provide strategic guidance on AI adoption, ethics, and governance within the organization. Advise on AI-driven business models, innovation strategies, and regulatory compliance. Evaluate AI research, development, and deployment strategies to ensure ethical and sustainable growth. Mentor and collaborate with internal teams on best practices in AI, data science, and machine learning. Assess AI risks, biases, and challenges, providing solutions for responsible AI implementation.

Key Responsibilities: Provide strategic guidance on AI adoption, ethics, and governance within the organization. Advise on AI-driven business models, innovation strategies, and regulatory compliance. Evaluate AI research, development, and deployment strategies to ensure ethical and sustainable growth. Mentor and collaborate with internal teams on best practices in AI, data science, and machine learning. Assess AI risks, biases, and challenges, providing solutions for responsible AI implementation.

AECOM is seeking a mid-level Environmental Database Manager with a minimum of 6 years of experience to support our enterprise environmental data management system (EarthSoft EQuIS). The ideal candidate will have a strong understanding of environmental data and terminology, good communication skills, and the ability to collaborate with both technical and non-technical stakeholders. This position will offer a hybrid work arrangement to include both office and remote work schedules and will be based from our office located in Bengaluru, India. This role includes, but is not limited to, the following activities: Responsibilities: The ideal candidate will beable to understandrequests fromenvironmental subjectmatter experts. Gather, organize, and validate field data from environmental monitoring activities such as air, soil, and water quality assessments. Manage field and analytical data in relational database systems like EarthSoft EQuIS, Locus EIM or other environment databases. Conducting QA/QC for electronic data deliverables with laboratory analytical data to ensure quality. Generating standardized report outputs through software tools like EQuIS or EIM. Prepare environment data summaries and compliance reports for submission to regulatory agencies. Utilize statistical tools and predictive modeling techniques to assess environmental impacts and forecast trends. Design and create dashboards and visualizations using platforms such as Power BI or EQuIS Enterprise. Ensure data meets reporting standards and guidelines set by local, state, and federal authorities. Responsible for generating Borelogs through multiple platforms like gINT, open source or EQuIS. Supporting legacy data migrations to EQuIS/EIM as needed, ensuring proper formatting and compatibility. Collaborate with stakeholders, project managers, and team members, to achieve project objectives efficiently. Provide technical support to field sampling teams and act as a liaison between the project staff, analytical laboratory, data validator, and GIS analysts. Research state and federal regulations necessary to manage action levels or clean-up criteria. Qualifications Qualifications: Bachelors degree in environmental engineering, environmental science, or related discipline and 6+ years of relevant experience in environmental data management or consulting, with hands-on experience in EQuIS, LOCUS, EIM, ESDAT, or similar databases or demonstrated equivalency of education and/or experience. Skills Required: Expertise and experience with environmental data and database systems (MS SQL Server, MS Access). Expertise with relational databases such as EarthSofts Environmental Quality Information System (EQuIS) /EIM/ ESdat. Ability to continually analyze data at all stages for problems, logic, and consistency concerning field data collection, analytical reporting, and other expertise on EQUIS sub-tools (Collect, Edge, ArcGIS highly desirable but not essential). Assist projects globally and task delivery with high quality and within deadlines. Managing data (geological, Field data, chemical laboratory data) for technical report writing and interpretation as required by the team. Maintaining and updating various project dashboards using the web-based EQuIS Enterprise system; and preparing report-ready data tables, charts, and figures for internal review and external client reports. Project management duties include coordinating field events. Using the sample registry and Sample Planning module create EDDs and load to EQuIS to track event closure. Proficient in EQuIS collect Module, create and deploy different categories of forms and train field personnel on the same. Expert level understanding of Office 365, Excel, power query & Power automation. Should be good in Documentation including Data Management SOPs, Process Maps, Work instructions, Activity Analysis, Task effort estimation Use of visualization tools like Power BI to help management to make effective decisions for the environmental domain is desirable but not essential Knowledge of digital tools like Power BI, R Studio, KNIME Analytics, Python is a plus but not mandatory. Strong organizational skills, with experience prioritizing, time management and managing multiple tasks. Effective communication skills to interact with multidisciplinary teams and clients. Expertise in applying Six-Sigma techniques/analysis to the environmental data management process. Strong attention to detail with excellent analytical, judgment and problem-solving capabilities. Comfortable running meetings and presentations Preferred Qualifications: Masters degree in environmental engineering, Environmental Science, or a related discipline. Min 6 - 10 years of relevant experience in environmental data management or consulting, with hands-on experience in EQuIS, LOCUS, EIM, ESDAT, or similar databases or demonstrated equivalency of education and/or experience. Additional Information About AECOM AECOM is proud to offer comprehensive benefits to meet the diverse needs of our employees. Depending on your employment status, AECOM benefits may include medical, dental, vision, life, AD&D, disability benefits, paid time off, leaves of absences, voluntary benefits, perks, flexible work options,well-being resources, employee assistance program, business travel insurance, service recognition awards, retirement savings plan, and employee stock purchase plan. AECOM is the global infrastructure leader, committed to delivering a better world. As a trusted professional services firm powered by deep technical abilities, we solve our clients complex challenges in water, environment, energy, transportation and buildings. Our teams partner with public- and private-sector clients to create innovative, sustainable and resilient solutions throughout the project lifecycle from advisory, planning, design and engineering to program and construction management. AECOM is a Fortune 500 firm that had revenue of $16.1 billion in fiscal year 2024. Learn more at aecom.com. What makes AECOM a great place to work You will be part of a global team that champions your growth and career ambitions. Work on groundbreaking projects - both in your local community and on a global scale - that are transforming our industry and shaping the future. With cutting-edge technology and a network of experts, youll have the resources to make a real impact. Our award-winning training and development programs are designed to expand your technical expertise and leadership skills, helping you build the career youve always envisioned. Here, youll find a welcoming workplace built on respect, collaboration and community - where you have the freedom to grow in a world of opportunity. As an Equal Opportunity Employer, we believe in your potential and are here to help you achieve it.

Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together. We are seeking a dynamic and skilled Lead AIML Engineer who is passionate about solving real world problems in the healthcare domain using cutting edge capabilities and emerging technologies. As a Lead AI/ML Engineer, the candidate will be responsible for developing AI business case, solution design and collaborating with other senior leaders, stakeholders, and customers to ensure alignment, integration of AI/ML capabilities with mentoring and leading the Data Science resources for contact analytics area. The Ideal Candidate will follow advancements in the state-of-the-art methods that are relevant to the particular use case and provide recommendations for model development and experimentation. Primary Responsibilities: Lead Artificial Intelligence (AI) Engineer Design innovative AI solutions to various business problems, utilizing cutting-edge AI technologies like Generative AI, Large Language Models, RAG, Reinforcement learning, Agentic AI Communicating analytics model behavior/results to Stakeholders Carrying out technical risk analysis and reliability assessments Mentor, Guide the team of scientists, data analysts, and business stakeholders to design and deploy AI solutions Develop and demonstrate AI use-cases, conducting workshops and training sessions to foster AI adoption Take a leadership role in the data science community of experts Evaluate and implement best practices in AI/ML, data mining, and analytics Document architecture roadmaps, reference architectures, and standard operating procedures for AI solutions Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so Required Qualifications Master’s degree in computer science, Computer Engineering, Data Science, Information Technology, or related field 10+ years of work experience with at least one of the following languagesPython, Java, and R 5+ years of experience in high-level architecture design and solution development for large-scale AI/ML systems Extensive experience with deep learning frameworks (e.g., TensorFlow, Keras, PyTorch), time series analysis, predictive modeling, and NLP Experience and knowledge of Large Language Models, RAG, Transformers Comprehensive knowledge of modern data science and product/web analytics tools and tehcniques including python and associated data science ecosystem, machine learning, Azure Machine Learning etc. Broad knowledge and understanding of advanced statistical, machine learning, and/or data mining techniques Knowledge of both traditional machine learning algorithms and modern deep learning and generative AI models and methods Knowledge of both traditional machine learning algorithms and modern deep learning and generative AI models and methods Knowledge of high-performance AI computing platforms, Linux, and shell scripting in AI computing environments Knowledge of Cloud platform supporting AI Implementation like Azure ML Studio Proficiency in Python for AI/ML; experience with graph databases, neural networks, and MLOps Proven track record in industry use cases utilizing deep and machine learning techniques Demonstrated ability to develop and manage complex projects, leading an interdisciplinary team to achieve project goals Demonstrated ability to provide mentorship and guidance for the efficient and technical development of the members of your team Demonstrated ability to develop and manage complex projects, leading an interdisciplinary team to achieve project goals Demonstrated ability to provide mentorship and guidance for the efficient and technical development of the members of your team Proven expertise in predictive analytics, machine learning, deep learning architecture, Large Language Models, RAG, and text analytics with NLP Proven exceptional communication skills to articulate technical solutions to both technical and non-technical audiences Proven strategic thinking in systems capacity planning, hardware and software updates, and migration At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone-of every race, gender, sexuality, age, location and income-deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes — an enterprise priority reflected in our mission.

Optum AI is UnitedHealth Group’s enterprise AI team. We are AI/ML scientists and engineers with deep expertise in AI/ML engineering for health care. We develop AI/ML solutions for the highest impact opportunities across UnitedHealth Group businesses including UnitedHealthcare, Optum Financial, Optum Health, Optum Insight, and Optum Rx. In addition to transforming the health care journey through responsible AI/ML innovation, our charter also includes developing and supporting an enterprise AI/ML development platform. Optum AI Team Members Have impact at scaleWe have the data and resources to make an impact at scale. When our solutions are deployed, they have the potential to make health care system work better for everyone. Do ground-breaking workMany of our current projects involve cutting edge ML, NLP and LLM techniques. Generative AI methods for working with structured and unstructured health care data are continuously being developed and improved. We are working in one of the most important frontiers of AI/ML research and development. Partner with world-class experts on innovative solutionsOur team members are developing novel AI/ML solutions to business challenges. In some cases, this includes the opportunity to file patents and publish papers about the methods we develop. We also collaborate with AI/ML researchers at some of the world’s top universities. OptumAI is looking for a Senior Machine Learning Engineer with deep subject matter expertise in text processing, NLU and SLU (Natural language understanding and Spoken Language Understanding) who will be part of a team leading the technical development and inventions that allow Optum machine learning products drive positive impact in the healthcare business. Your expertise will bring business and industry context to science and technology decisions. As part of the OptumAI AI/ML engineering group, you set the standard for scientific excellence and make decisions that affect the way we build and integrate algorithms. Your code, designs and documents are exemplary and are used as references across the organization. A successful candidate is a hands-on AI/ML engineering expert that will tackle intrinsically hard problems, acquiring expertise as needed. The candidate will help decompose complex problems into straightforward solutions. Primary Responsibilities Help design and develop the next generation of NLP, ML & AI products, and services for healthcare Develop machine learning and deep learning models and systems in domains including, but not limited toNLP, NLU, NLG, SLU and multidimensional time series forecasting among others Exposure in RAG, LangChain, VectorDBs Ability to Quantize, Optimize GenAI models Manage NLP & ML models lifecycle for a suite of products Run large complex proof-of-concepts for the healthcare business Manage prioritization and technology work for building NLP, ML & AI solutions Lead the full end-to-end machine learning development process including data ingestion and preparation, feature engineering, analysis and modeling, model deployment, performance tracking and documentation Establish best practices for end-to-end deep learning and machine learning development cycle to ensure rigor in process and quality in outcome Work with a great deal of autonomy to find solutions to complex problems Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so Required Qualifications Graduate degree in applicable area of expertise or equivalent experience Experience in deploying scalable solutions to complex problems, from defining the problem, implementing the solution, and launching the new product successfully Skill Set; NLP, NLU, NLI ArchitectureTransformers, Attention ModelsGPT, Llama, Mistral Model Quantization Model Optimization Retrieval & Ranking, RAG, RAGAS Statistics, Machine Learning Models, Model Deployment Proven excellent communication, writing and presentation skills Experience in the health care industry Preferred Qualification Experience in the health care industry At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone-of every race, gender, sexuality, age, location and income-deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes — an enterprise priority reflected in our mission. #Nic

Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together. Primary Responsibilities Lead AI or ML projects from conception to deployment, ensuring high-quality and scalable solutions Design and develop predictive and prescriptive models using advanced machine learning techniques Apply knowledge of statistics, programming, data modeling, and simulation to recognize patterns and identify opportunities Collaborate with engineers and other stakeholders to build statistical models and apply machine learning techniques for targeted solutions Conduct exploratory data analysis on unstructured, diverse datasets to drive innovative solutions Use analytics and statistical software such as SQL, R, Python, Hadoop, and others to perform analysis and interpret data Provide expertise in modeling and statistical approaches, including regression methods, decision trees, deep learning, NLP techniques, and uplift modeling Develop and evaluate predictive and prescriptive models and advanced algorithms to extract optimal value from data Communicate analysis and findings through interactive visualizations, documents, and presentations Mentor and guide junior data scientists, fostering a culture of continuous learning and improvement Stay updated with the latest advancements in AI/ML and data science, and apply them to improve existing solutions Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so Required Qualifications Master's or Bachelor's degree in Computer Science, Statistics, Engineering, Mathematics, or a related field Proven experience in AI/ML projects, with hands-on experience in coding and deploying AI/ML solutions Experience to deploy and manage AI/ML applications preferable Azure or GCP Proficiency in statistical techniques, machine learning methods, and relevant technologies Proven solid programming skills in languages such as Python, R, SQL, and experience with big data tools like Hadoop Proven excellent analytical and problem-solving skills, with the ability to work with large amounts of data Proven effective communication skills, with the ability to present complex findings in a clear and concise manner Proven self-motivated, curious, and innovative, with a strong ability to work independently and as part of a team At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone-of every race, gender, sexuality, age, location and income-deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes — an enterprise priority reflected in our mission.

Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by diversity and inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health equity on a global scale. Join us to start Caring. Connecting. Growing together Primary Responsibilities Applying knowledge of statistics, machine learning, programming, data modeling, simulation, and advanced mathematics to recognize patterns, identify opportunities, pose business questions, and make valuable discoveries leading to prototype development and product improvement Data mining using state-of-the-art methods Enhancing data collection procedures to include information that is relevant for building analytic systems Processing, cleansing, and verifying the integrity of data used for analysis Doing ad-hoc analysis and presenting results in a clear manner Working with analytics and statistical software such as SQL, R, Python, Hadoop and others to perform analysis and interpret data Work with stakeholders to identify opportunities for leveraging company data to drive business solutions. Mine and analyze data from company databases to drive optimization and improvement of product development, marketing techniques and business strategies Assess the effectiveness and accuracy of new data sources and data gathering techniques Develop custom data models and algorithms to apply to data sets Use predictive modeling to increase and optimize customer experiences, revenue generation, ad targeting and other business outcomes Develop company A/B testing framework and test model quality Coordinate with different functional teams to implement models and monitor outcomes Develop processes and tools to monitor and analyze model performance and data accuracy Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so Required Qualifications Graduate degree or equivalent experience Experience using statistical computer languages (R, Python, SLQ, etc.) to manipulate data and draw insights from large data sets Experience working with and creating data architectures Experience querying databases and using statistical computer languagesR, Python, SLQ, etc. Experience using web servicesRedshift, S3, Spark, DigitalOcean, etc. Experience creating and using advanced machine learning algorithms and statisticsregression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc. Experience with distributed data/computing toolsMap/Reduce, Hadoop, Hive, Spark, Gurobi, MySQL, etc. Experience visualizing/presenting data for stakeholders usingPeriscope, Business Objects, D3, ggplot, etc. Solid problem solving skills with an emphasis on product development Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications Proven excellent written and verbal communication skills for coordinating across teams A drive to learn and master new technologies and techniques Coding knowledge and experience with several languagesC, C++, Java, JavaScript, etc. Knowledge and experience in statistical and data mining techniquesGLM/Regression, Random Forest, Boosting, Trees, text mining, social network analysis, k-NN, Naive Bayes, SVM, etc. At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone - of every race, gender, sexuality, age, location and income - deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission.

Key Responsibilities Develop and implement a comprehensive analytics strategy aligned with organizational objectives. Lead cross-functional projects using advanced data modeling and analysis techniques to uncover strategic insights and process optimization opportunities. Design, build, and maintain data models, dashboards, reporting systems, and performance metrics to support key business decisions. Drive critical business processes such as demand forecasting and the Sales & Operations Planning (S&OP) process. Generate actionable sales recommendations for the trade sales team. Optimize business processes like supply chain networks and inventory management through predictive and prescriptive data modeling. Oversee the delivery of analytical reports and performance insights across functions. Manage and streamline processes related to data intake, validation, mining, engineering, visualization, and reporting. Anticipate and plan for future analytical needs related to people, technology, budgeting, and business objectives. Apply advanced analytics techniques to enhance commercial routines and decision-making. Lead data insight initiatives and ensure effective stakeholder collaboration. Clearly communicate the impact of analytics-driven insights across internal and external teams. Perform critical analysis and deliver actionable business recommendations. Educational Qualifications B.E./B.Tech/M.Tech in Computer Science, Statistics, Data Management, or Business Intelligence OR MBA/PGDM in Data Science, Business Analytics, Business Intelligence, Sales, or Marketing Work Experience Minimum 4+ years of experience in data analytics, including monitoring, managing, manipulating, and drawing insights from complex datasets. Proven track record working with data visualization tools such as Power BI, Tableau, Raw, or chart.js. Preferred/Additional Requirements Strong understanding of data mining principles, predictive analytics, and integrating data from multiple sources (on-premises and cloud-based). Experience with analytical and statistical techniques including hypothesis development, A/B testing, data analysis, and drawing conclusions. Ability to generate actionable insights and recommendations for business units. Team Structure Will work closely with multiple vendor teams . Key Interfaces Internal: Supply Chain, Sales, and Finance Teams External: Analytics vendors Functional Competencies Strong problem-solving and quantitative analysis skills Ability to manage multiple projects, processes, and cross-functional teams simultaneously Excellent collaboration, communication, and stakeholder management skills Behavioral Competencies Critical Thinking: Ability to evaluate complex issues, make informed decisions, and deliver innovative solutions Professionalism: Demonstrates integrity, accountability, strong work ethic, and ethical behavior

Key Responsibilities: Provide strategic guidance on AI adoption, ethics, and governance within the organization. Advise on AI-driven business models, innovation strategies, and regulatory compliance. Evaluate AI research, development, and deployment strategies to ensure ethical and sustainable growth. Mentor and collaborate with internal teams on best practices in AI, data science, and machine learning. Assess AI risks, biases, and challenges, providing solutions for responsible AI implementation.

We are seeking a highly skilled AI Engineer with demonstrated expertise in both traditional Machine Learning modelling and modern GenAI techniques. This role involves building scalable AI systems using foundation models, parameter- efficient fine-tuning (PEFT), and robust MLOps pipelines, while also grounding your solutions in classical machine learning principles. The ideal candidate excels at blending structured data modelling with large language model capabilities to drive intelligent, efficient, and production-ready AI systems. Key Responsibilities: Design, build, and deploy predictive systems by combining traditional ML models (e.g., regression, tree-based, time series) with Generative AI capabilities (e.g., LLMs, embeddings, GenAI-based simulation). Strong skills in prompt engineering are required to support the development and deployment of generative AI solutions. Fine-tune foundation models using PEFT techniques (e.g., LoRA, prefix tuning, adapters) for domain-specific applications. Build and maintain end-to-end MLOps pipelines for model versioning, testing, deployment, monitoring, and retraining. Use LLMs for automating feature generation, synthetic data creation, and prompt-driven scenario modelling. Manage the full AI/ML model lifecycle: experimentation, deployment, monitoring, diagnostics, and iterative enhancements. Apply and validate classical ML algorithms (e.g., XGBoost, LightGBM, ARIMA, SVMs, etc.) as benchmarks or hybrid components. Collaborate with cross-functional teams (data scientists, ML engineers, DevOps, product) to deliver AI solutions aligned with business needs. Deploy and monitor solutions in cloud environments (e.g., AWS SageMaker, GCP Vertex AI, Azure ML, REST(FAST API) with automated retraining and model health checks. Required Skills and Qualifications: Bachelors or Master’s degree in Computer Science, Machine Learning, Data Science, or related field. 3+ years of experience in AI/ML engineering, with proven success in both traditional predictive modelling and LLM-based development. Strong Python programming skills and familiarity with ML libraries such as scikit-learn, XGBoost, LightGBM, PyTorch, and Transformers. Experience in parameter-efficient fine-tuning (PEFT) using frameworks such as Hugging Face PEFT, QLoRA, or AdapterHub. Proficiency in building MLOps workflows with tools like MLflow, Airflow, Kubeflow, or SageMaker Pipelines. Solid SQL/NoSQL experience and strong data wrangling skills. Hands-on experience deploying models in production cloud environments and containerized systems (e.g., Docker, Kubernetes). Excellent problem-solving, debugging, and communication skills.

Job Summary We are seeking an AI Leader for building Guardrail Platform to drive the design, deployment, and governance of AI guardrails that ensure ethical, responsible, and compliant AI operations . This role involves collaborating with cross-functional teams to implement AI fairness, explainability, bias mitigation, security, and regulatory compliance frameworks across AI/ML pipelines. Roles & Responsibilities AI Guardrail Strategy & Implementation Define and implement AI guardrails to ensure ethical AI development, risk mitigation, and compliance. Establish automated monitoring for AI fairness, bias detection, and explainability. Lead the operationalization of Responsible AI (RAI) principles across the organization. AI Risk & Compliance Management Align AI models with regulatory standards (e.g., GDPR, AI Act, CCPA, NIST AI RMF). Develop governance frameworks for model validation, auditing, and risk assessment . Collaborate with legal, compliance, and security teams to ensure AI transparency. AI Model Security & Reliability Implement guardrails against adversarial attacks, data poisoning, and model drift . Establish secure AI deployment standards to prevent unauthorized AI model access or misuse. Establish DevSecOps pipeline teams to integrate AI security best practices . Operationalization & AI Governance Define AI monitoring KPIs for continuous risk assessment and compliance tracking. Develop automated pipelines to flag high-risk AI behaviors and decision anomalies. Foster a culture of explainable AI (XAI) & transparency for AI-driven decision-making. Cross-functional Leadership & Innovation Partner with product, legal, and engineering teams to integrate AI guardrails into MLOps workflows . Stay ahead of AI regulatory trends, industry best practices, and emerging risks . Competencies Required Skills Education Skills (NOT TO BE USED)

Participate in client engagements in enhancing current statistical models and develop new models for business needs or design of experiments for test/control analysis and business process trials. Consult with cross-functional teams on matters relating to Machine Learning, knowledge discover, data modeling, and analytics. Own predictive models/ML and DOE/A-B testing areas of production ready ML models hosted across multiple systems. Develop business context for environment and ML uses/applications and deep knowledge of data inputs, outputs, and statistical testing/modeling Write/Run data extraction algorithms to acquire data from primary or secondary data sources and ability to describe/direct data requests for representative data necessary for analyses Develop statistical tests and predictive solutions to make business recommendations for decisioning Train/develop models, run evaluation experiments, and perform statistical analysis of results, refine and test / validate models in production Develop understanding of data framework and how it relates to business use, specific process time points, and make recommendations for any new data needs. Coordinate with data engineers to ensure data is representative of analysis solutions. Use of data analytics and other strategies that optimize statistical efficiency and quality Interpret data, analyze results using statistical techniques and provide ongoing reports Identify, analyze, and interpret trends or patterns in complex data sets Work with management to prioritize business and information needs Perform Ad Hoc Data Analysis and reporting for model performance Locate and define new process improvement opportunities for testing and predictive modeling Qualifications Required / Desired Skills Advanced degree in one or more quantitative discipline Operations Research, Stats, Math, Comp Sci, Engineering, Economics or similar Experience in developing a variety of machine learning models algorithms in a commercial environment with a track record of creating meaningful business impact. Proficient with Pyspark, noSQL and Python and distributed programming Expertise working in MongoDb, Snowflake, Databricks and cloud computing platforms (AWS, GCP or Azure), or equivalent on-premise platform and deployment Experience in client engagements, interpreting client s business challenges, and recommendations for statistical analysis solutions (ie analytical consulting and solution design) Experience in presentation design, development, delivery, and communication skills to present analytical results and recommendations for action-oriented data driven decisions and associated operational and financial impacts. Experience in Gen AI, LLM Workflow, Graph RAG etc is an added advantage. Flexible to work in shift model.

Key Responsibilities: Provide strategic guidance on AI adoption, ethics, and governance within the organization. Advise on AI-driven business models, innovation strategies, and regulatory compliance. Evaluate AI research, development, and deployment strategies to ensure ethical and sustainable growth. Mentor and collaborate with internal teams on best practices in AI, data science, and machine learning. Assess AI risks, biases, and challenges, providing solutions for responsible AI implementation.

Key Responsibilities: Provide strategic guidance on AI adoption, ethics, and governance within the organization. Advise on AI-driven business models, innovation strategies, and regulatory compliance. Evaluate AI research, development, and deployment strategies to ensure ethical and sustainable growth. Mentor and collaborate with internal teams on best practices in AI, data science, and machine learning. Assess AI risks, biases, and challenges, providing solutions for responsible AI implementation.

Key Responsibilities: Provide strategic guidance on AI adoption, ethics, and governance within the organization. Advise on AI-driven business models, innovation strategies, and regulatory compliance. Evaluate AI research, development, and deployment strategies to ensure ethical and sustainable growth. Mentor and collaborate with internal teams on best practices in AI, data science, and machine learning. Assess AI risks, biases, and challenges, providing solutions for responsible AI implementation.

Findability Sciences is looking for Data Scientist to join our dynamic team and embark on a rewarding career journey. Undertaking data collection, preprocessing and analysis Building models to address business problems Presenting information using data visualization techniques Identify valuable data sources and automate collection processes Undertake preprocessing of structured and unstructured data Analyze large amounts of information to discover trends and patterns Build predictive models and machine-learning algorithms Combine models through ensemble modeling Present information using data visualization techniques Propose solutions and strategies to business challenges Collaborate with engineering and product development teams

Sberbank is looking for Senior Data Scientist to join our dynamic team and embark on a rewarding career journey. Undertaking data collection, preprocessing and analysis Building models to address business problems Presenting information using data visualization techniques Identify valuable data sources and automate collection processes Undertake preprocessing of structured and unstructured data Analyze large amounts of information to discover trends and patterns Build predictive models and machine-learning algorithms Combine models through ensemble modeling Present information using data visualization techniques Propose solutions and strategies to business challenges Collaborate with engineering and product development teams

Why We Work at Dun Bradstreet Dun Bradstreet unlocks the power of data through analytics, creating a better tomorrow. Each day, we are finding new ways to strengthen our award-winning culture and accelerate creativity, innovation and growth. Our 6,000+ global team members are passionate about what we do. We are dedicated to helping clients turn uncertainty into confidence, risk into opportunity and potential into prosperity. Bold and diverse thinkers are always welcome. Come join us! Learn more at dnb.com/careers . The Role: As part of Dun Bradstreets Data Analytics team, you will participate in all aspects of modeling engagement, including design, development, validation, calibration, documentation, approval, implementation, monitoring, and reporting. You will research complex business issues and recommend solutions, including model features, end products and any data required to support growing Dun Bradstreet initiatives. Key Responsibilities: Utilize the latest data science techniques across both supervised and unsupervised machine learning methodologies, Natural Language Processing, and graph analysis in automating and scaling internal business processes. Establish and maintain strong relationships with key business stakeholders. Engage clients and DB colleagues to identify business needs and develop, implement, and manage solutions. Strong communication skills and the ability to simplify and explain complex concepts for stakeholders, clients, and senior leaders. Participate in all aspects of a modeling engagement, including design, data requirements, development, validation, calibration, documentation, approval, implementation, monitoring and reporting. Develop Global Analytic Solutions inclusive but not limited to statistical models based on DB s established best practices, methodologies, and tools. Research complex business issues and recommend solutions, including model inputs and end products, focusing on addressing specific customer needs and use cases. Serve as a Subject Matter Expert on predictive models within the team and with business users; consult with the business, as appropriate, on predictive modeling solutions. Enjoy and share academic literature and industry best practices. Identify business relevance of new methods and work with cross functional teams to create prototypes, assist in creating business cases and go to market strategies. Validate the performance of existing quantitative risk models and recommend changes when necessary. Drive timely retrieval of risk analytics data from existing systems to create algorithms that meet business needs. Key Skills Master s Degree or Ph.D. in a quantitative/applied field preferred (Statistics, Econometrics, Computer Science, Operations Research, Mathematics, Engineering). 7+ years operating successfully in data science roles, especially roles requiring cross-company collaboration and disciplined delivery of initiatives. Hands-on experience applying modern machine learning techniques. Ability to program in other statistical analysis languages, proficiency in programming languages (Python, R, SQL). Experience in feature engineering, automation, network analysis or Natural Language Processing. Experience working with outside clients on statistical engagements. Ability to manage multiple assignments, many of which have challenging timelines. Ability to work independently, as well as collaborate effectively in a team environment. Excellent communication and presentation skills. Proficiency in Microsoft Office Suite. Show an ownership mindset in everything you do. Be a problem solver, be curious and be inspired to take action. Be proactive, seek ways to collaborate and connect with people and teams in support of driving success. Continuous growth mindset, keep learning through social experiences and relationships with stakeholders, experts, colleagues and mentors as well as widen and broaden your competencies through structural courses and programs. Where applicable, fluency in English and languages relevant to the working market. . .

We are looking for a highly skilled and experienced Credit Officer to join our team at Equitas Small Finance Bank Ltd. The ideal candidate will have 2 to 7 years of experience in the BFSI industry, with expertise in credit operations. Roles and Responsibility Manage and process loan applications according to company policies and procedures. Conduct thorough credit analysis and risk assessments to determine client creditworthiness. Develop and maintain relationships with existing clients to ensure timely payments and resolve any issues that may arise. Collaborate with internal teams to identify new business opportunities and grow the bank's customer base. Monitor and report on credit portfolio performance, identifying areas for improvement and implementing strategies to mitigate risks. Ensure compliance with regulatory requirements and industry standards in all credit-related activities. Job Requirements Strong knowledge of credit operations, including credit scoring, underwriting, and risk assessment. Excellent communication and interpersonal skills, with the ability to build strong relationships with clients and colleagues. Proficiency in Microsoft Office and other banking software applications. Ability to work in a fast-paced environment, meeting deadlines and achieving targets. Strong analytical and problem-solving skills, with attention to detail and accuracy. Experience working in a similar role within the BFSI industry is preferred.

We are looking for a highly skilled and experienced Credit Analyst to join our team at Equitas Small Finance Bank Ltd. The ideal candidate will have 1-2 years of experience in the BFSI industry. Roles and Responsibility Analyze credit data to determine client creditworthiness. Develop and maintain relationships with clients to understand their financial needs. Conduct thorough credit risk assessments and provide recommendations. Collaborate with cross-functional teams to develop and implement credit policies. Monitor and report on credit portfolio performance metrics. Stay up-to-date with industry trends and regulatory changes affecting credit analysis. Job Requirements Strong understanding of credit principles, including credit scoring and risk modeling. Excellent analytical and problem-solving skills with attention to detail. Ability to work effectively in a fast-paced environment and meet deadlines. Strong communication and interpersonal skills, with the ability to build rapport with clients. Proficiency in credit management software and Microsoft Office applications. Ability to think critically and make sound decisions under pressure.

Research in Nokia Standards (NSD) comprises fundamental systematic research of an exploratory nature for developing new products and services as well as disruptive technologies superseding conventional approaches. It covers the provision of a comprehensive understanding of scientific insights, specifically leading to (pre-) standardization of ideas and concepts for 6G technologies and beyond. In light of the recent advancements in artificial intelligence (AI) and data monetization, 6G will be the first mobile system built around and for datafirst, 6G will be the first generation of fully AI-native mobile systems where new AI features will enhance traditional solutions. Secondly, 6G will be designed according to a data-driven approach, where quantitative data and measures collected in past releases will help in shaping the design of 6G. Thirdly, 6G will be conceived to convert the massive data generated by mobile systems into valuable and monetizableinformation. You must have: Strong technical background in data science and modern data management techniques. Solid knowledge of data analysis techniques to analyze data generated in wireless systems to optimize their performance. Proven experience in data engineering methods to represent data including hands-on experience in developing data management and AI tools. Excellent written and interpersonal communication skills. Leadership and collaborative mindset with the ability to work autonomously. Strong professional ethics, open communication, and ability to rectify mistakes quickly. It would be nice if you also had: Knowledge of language processing techniques (NLP, GenAI, transformers) including hands-on experience of the tools. Experience in simulation of dynamic systems, especially for wireless communication systems (link and/or system level). Hands-on experience with AI/ML techniques applied to wireless communication. Proven software development skills with C/C++ programming language. Proven track record of innovation like publications in top conferences and journals. Drive data science progress in 6G technology and build the next generation mobile systems around modern data management approaches. Drive progress as a technical lead, contributing to new products, processes, and standards on data science for future 6G systems. Work with a world-class team to drive 6G technologies in global standardization. Carry out specialized activities/projects, demonstrating adaptability in complex business environments. Communicate within and outside the team, influencing others to accept new concepts and practices.

Strong proficiency in Python and/or R for data analysis and modeling. Advanced SQL skills for data querying and transformation. Hands-on experience with machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch). Solid understanding of statistics, hypothesis testing, regression analysis, and data mining. Familiarity with cloud platforms (AWS, Azure, or GCP) and big data tools (Spark, Hadoop) is a plus. Excellent problem-solving skills and attention to detail.

Boston Consulting Group partners with leaders in business and society to tackle their most important challenges and capture their greatest opportunities. BCG was the pioneer in business strategy when it was founded in 1963. Today, we help clients with total transformation-inspiring complex change, enabling organizations to grow, building competitive advantage, and driving bottom-line impact. To succeed, organizations must blend digital and human capabilities. Our diverse, global teams bring deep industry and functional expertise and a range of perspectives to spark change. BCG delivers solutions through leading-edge management consulting along with technology and design, corporate and digital ventures and business purpose. We work in a uniquely collaborative model across the firm and throughout all levels of the client organization, generating results that allow our clients to thrive. What Youll Do As a Senior Manager within Audience Insight and Marketing Analytics, you will lead customer insights and marketing analytics efforts within BCG s global digital marketing team. Your role will be crucial in scaling ability to leverage audience insights to shape marketing strategies, optimize audience engagement, and enhance personalization efforts across BCG s campaigns as well as provide direction to shape analytical products to deliver insights to internal stakeholders. You will be responsible for integrating and analyzing data from multiple marketing channels and platforms, developing audience segmentation models, and applying predictive analytics to uncover trends and behaviors. The insights generated will guide marketing leadership in making data-informed decisions, improving campaign effectiveness, and refining BCG s content and engagement strategies.. Considering that this is a global role, the expectation would be that you would be willing to work 11am to 8pm IST to have overlap with our global colleagues. KEY RESPONSIBILITIES Data Integration and Analysis: Collect, integrate, and analyze data from various marketing channels, CRM platforms, Snowflake, Demandbase, and other data sources. Ensure data accuracy and integrity by conducting audits and validations. Use statistical methods, machine learning models, and predictive analytics to identify audience trends and behaviors. Insight Generation: Develop audience segmentation insights and findings based on behavioral, engagement, and firmographic data. Conduct in-depth marketing funnel analysis to optimize customer engagement and conversion rates. Translate complex data sets into clear, actionable insights that inform marketing strategies and business decisions. Identify opportunities for campaign optimization, persona refinement, and content strategy improvements. Support for Marketing Initiatives: Lead audience-focused data analytics to enhance global marketing campaigns and always-on marketing activities. Provide data-driven recommendations for audience engagement, content targeting, and personalization strategies. Support persona and customer journey development through robust data analysis. Metrics Analysis and Reporting: Develop and maintain real-time dashboards and reports in Tableau and Power BI to track key audience and engagement metrics. Conduct thorough performance analysis of marketing campaigns, identifying trends and areas for optimization. Present insights and data interpretations to stakeholders through clear visualizations, reports, and executive briefings. Monitor and report on the effectiveness of marketing strategies and audience segmentation approaches. Cross-Functional Collaboration and Communication: Partner with CX, content, and digital marketing teams to refine customer insights and improve engagement strategies. Act as a trusted advisor to senior marketing leadership, ensuring data insights drive decision-making. Work closely with data science, analytics, and IT teams to enhance data infrastructure and analytics capabilities. Present findings and strategic recommendations to senior stakeholders. Process and Documentation Management: Develop and document best practices for data management, audience analytics, and reporting methodologies. Implement standard operating procedures for data collection, segmentation, and marketing attribution. Champion best practices for data-driven marketing strategies within the team and across global marketing functions. What Youll Bring 10+ years of experience in marketing analytics, audience insights, or data-driven strategy roles Demonstrated expertise in paid/earned/owned channels a plus Expertise in data visualization tools (Tableau, Power BI) and marketing analytics platforms Hands-on experience with CRM systems, Snowflake, Demandbase, Google Analytics, and other marketing data sources Advanced skills in marketing funnel optimization, segmentation modeling, and campaign performance analysis Strong knowledge of Python/R for predictive modeling, statistical analysis, and audience segmentation Strong stakeholder management and ability to translate complex data into strategic recommendations Excellent communication and presentation skills for senior executives Experience in consulting, B2B marketing, or professional services industries is a plus Who Youll Work With You will work closely with members of Marketing Analytics and collaborate with BCG s CX, content, and digital marketing teams to refine audience insights and enhance marketing effectiveness. Additionally, you will partner with data science, analytics, and IT teams to improve data infrastructure and marketing analytics capabilities. ",

Leads GLOBAL DATA SCIENCE ADVANCED ANALYTICS within the Analytics Continuum Conceptualizes and builds predictive modeling, simulations, and optimization solutions to address business questions or use cases Applies ML and AI to analytics algorithms to build inferential and predictive models allowing for scalable solutions to be deployed across the business Conducts model validations and continuous improvement of the algorithms, capabilities, or solutions built Deploys models using Airflow, Docker on Google Cloud Platforms You connect the dots - Merge multiple data sources and build Statistical Models / Machine Learning models in Price and Promo Elasticity Modeling, Marketing Mix Modeling to derive actionable business insights and recommendation Assemble large, sophisticated data sets that meet functional / non-functional business requirements Build data and visualization tools for Business analytics to assist them in decision making You are a collaborator - Work closely with Division Analytics team leads Work with data and analytics specialists across functions to drive data solutions You are an innovator - Identify, design, and implement new algorithms, process improvements: while continuously automating processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc. Qualifications What you ll need BE/BTECH [ Computer Science, Information Technology is preferred ], MBA or PGDM in Business Analytics / Data Science, Additional DS Certifications or Courses, MSC / MSTAT in Economics or Statistics 5+ years of experience in building data models and driving insights Hands-on/experience on developing statistical models, such as linear regression, ridge regression, lasso, random forest, SVM, gradient boosting, logistic regression, K-Means Clustering, Hierarchical Clustering, Bayesian Regression etc. Hands on experience on coding languages Python(mandatory), R, SQL, PySpark, SparkR Strong Understanding of Cloud Frameworks Google Cloud, Snowflake and services like Kubernetes, Cloud Build, Cloud Run. Knowledge of using GitHub, Airflow for coding and model executions and model deployment on cloud platforms Working knowledge on tools like Looker, Domo, Power BI and web apps framework using plotly, pydash, sql Experience front facing Business teams (Client facing role) supporting and working with multi-functional teams in a dynamic environment What you ll need (Preferred) Managing, transforming, and developing statistical models for RGM/Pricing and/or Marketing Effectiveness Experience with third-party data i.e., syndicated market data, Point of Sales, etc. Working knowledge of consumer packaged goods industry Knowledge of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks. Experience visualizing/presenting data for partners using: Looker, DOMO, pydash, plotly, d3.js, ggplot2, pydash, streamlit etc Willingness and ability to experiment with new tools and techniques Ability to maintain personal composure and thoughtfully handle difficult situations. Knowledge of Google products (BigQuery, data studio, colab, Google Slides, Google Sheets etc)