1151 Statistical Modeling Jobs - Page 44

Location - All Genpact Locations Responsibilities Professional experience with different regression and classification methods in implementation and deployment of project on AWS GCP and Azure cloud platform. Follow the standard practice and guidelines while using Python, SQL. Experience with Langchain framework for GenAI. Develop and fine-tuning Generative AI models such as GPT for various applications. Using Generative AI to work on tasks like text generation, sentiment analysis, chatbots and language translation using RAG and agent-based models. Adjust language models that have already been trained for generative AI applications. Experience in tokenization and embeddings and must have used GPT, LLaMA, Huggingface, Mistral, AWS BedRock for deploying the models. Analyze data and Generating insights using generative AI techniques for predictive modelling and data generation. Building chatbot using different scalable data source for generating charts and statement. Having experience building front end application using Streamlit/Gradio/Flask/Fast for Generative AI input and output display. Responsible for weekly release of upgrades and new features to enhance current algorithm. Evaluating the performance of generative AI models and implementing improvements based on feedback. Ensuring ethical and responsible use of AI by addressing bias, privacy concerns and fairness in AI models. Must Demonstrate understanding of evaluation metrics specific to GenAI task such as inception score, frechet inception distance, perpetual path length. Collaborating with cross-functional teams, including data scientist, engineers, and domain experts to integrate Generative AI into product or services. Able to design Machine learning, Deep learning and Generative AI architecture and its successful execution in the project. Must have basic understanding on Word and Excel. Proficiency in programming language like Python, SQL, frameworks such as Langchain for AI model development. Experience on Rest API, Flask API, Fast API. Qualifications we seek in you!Minimum Qualifications / Skills Any Graduate BE/B- Tech, BCA, MCA, BSc/MSc Behavioral / team skills Personal drive and positive work ethic to deliver results within tight deadlines and in demanding situations Flexibility to adapt to a variety of engagement types, working hours and work environments and locations Excellent written, oral communication and presentation skills Bring a data-driven approach to decision making intellectually curious, always eager to learn new skills and share the knowledge with others Proactive planner and can work independently to manage own responsibilities Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color, religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values diversity and inclusion, respect and integrity, customer focus, and innovation. Get to know us at genpact.com and on LinkedIn, X, YouTube, and Facebook.Furthermore, please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a 'starter kit,' paying to apply, or purchasing equipment or training.

Ready to build the future with AI? At Genpact, we dont just keep up with technologywe set the pace. AI and digital innovation are redefining industries, and were leading the charge. Genpacts AI Gigafactory, our industry-first accelerator, is an example of how were scaling advanced technology solutions to help global enterprises work smarter, grow faster, and transform at scale. From large-scale models to agentic AI, our breakthrough solutions tackle companies most complex challenges. If you thrive in a fast-moving, innovation-driven environment, love building and deploying cutting-edge AI solutions, and want to push the boundaries of whats possible, this is your moment. Genpact (NYSE: G) is an advanced technology services and solutions company that delivers lasting value for leading enterprises globally. Through our deep business knowledge, operational excellence, and cutting-edge solutions – we help companies across industries get ahead and stay ahead. Powered by curiosity, courage, and innovation , our teams implement data, technology, and AI to create tomorrow, today. Get to know us at genpact.com and on LinkedIn, X, YouTube, and Facebook. Inviting applications for the role of Lead Consultant-Data Scientists with AI and Generative Model experience! We are currently looking for a talented and experienced Data Scientist with a strong background in AI, specifically in building generative AI models using large language models, to join our team. This individual will play a crucial role in developing and implementing data-driven solutions, AI-powered applications, and generative models that will help us stay ahead of the competition and achieve our ambitious goals. Responsibilities • Collaborate with cross-functional teams to identify, analyze, and interpret complex datasets to develop actionable insights and drive data-driven decision-making. • Design, develop, and implement advanced statistical models, machine learning algorithms, AI applications, and generative models using large language models such as GPT-3, BERT and also frameworks like RAG, Knowledge Graphs etc. Communicate findings and insights to both technical and non-technical stakeholders through clear and concise presentations, reports, and visualizations. Continuously monitor and assess the performance of AI models, generative models, and data-driven solutions, refining and optimizing them as needed. Stay up-to-date with the latest industry trends, tools, and technologies in data science, AI, and generative models, and apply this knowledge to improve existing solutions and develop new ones. Mentor and guide junior team members, helping to develop their skills and contribute to their professional growth. Qualifications we seek in you: Minimum Qualifications • Bachelor's or Master's degree in Data Science, Computer Science, Statistics, or a related field. Experience in data science, machine learning, AI applications, and generative AI modelling. Strong expertise in Python, R, or other programming languages commonly used in data science and AI, with experience in implementing large language models and generative AI frameworks. Proficient in statistical modelling, machine learning techniques, AI algorithms, and generative model development using large language models such as GPT-3, BERT, or similar frameworks like RAG, Knowledge Graphs etc. Experience working with large datasets and using various data storage and processing technologies such as SQL, NoSQL, Hadoop, and Spark. Strong analytical, problem-solving, and critical thinking skills, with the ability to draw insights from complex data and develop actionable recommendations. Excellent communication and collaboration skills, with the ability to work effectively with cross-functional teams and explain complex concepts to non-technical stakeholders. Preferred Qualifications/ skills • Experience in deploying AI models, generative models, and applications in a production environment using cloud platforms such as AWS, Azure, or GCP. Knowledge of industry-specific data sources, challenges, and opportunities relevant to Insurance Demonstrated experience in leading data science projects from inception to completion, including project management and team collaboration skills. Why join Genpact? Lead AI-first transformation – Build and scale AI solutions that redefine industries Make an impact – Drive change for global enterprises and solve business challenges that matter Accelerate your career —Gain hands-on experience, world-class training, mentorship, and AI certifications to advance your skills Grow with the best – Learn from top engineers, data scientists, and AI experts in a dynamic, fast-moving workplace Committed to ethical AI – Work in an environment where governance, transparency, and security are at the core of everything we build Thrive in a values-driven culture – Our courage, curiosity, and incisiveness - built on a foundation of integrity and inclusion - allow your ideas to fuel progress Come join the 140,000+ coders, tech shapers, and growth makers at Genpact and take your career in the only direction that matters: Up. Let’s build tomorrow together. Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color, religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values respect and integrity, customer focus, and innovation. Furthermore, please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a 'starter kit,' paying to apply, or purchasing equipment or training.

Position : Data Science Trainer Salary : As per company standards Experience : 1yr- 5yrs WORK FROM OFFICE MANDATORY (Full time, permanent) Notice Period : immediate Location : Pune Job Description : Candidates must have the ability to take both theory and practical sessions. Should have excellent knowledge on Python Data Science technologies. Should be able to teach Machine learning, deep learning, artificial Intelligence, SQL, Django .Able to resolve students' queries. We expect good communication and presentation skills. Able to explain complex subjects in a clear and interesting way. Dynamic personality. Should be flexible to conduct Weekend Batches as well as Weekday Batches. Responsibilities and Duties - Devise technical training programs according to organizational requirements. Produce training schedules and classroom agenda. Determine course content according to objectives. Prepare training material (presentations, worksheets etc.) Execute training sessions Keep and report data on completed courses, absences, issues etc. Observe and evaluate results of training programs. Determine overall effectiveness of programs and make improvements. (Note: No part time , No work from home) Interested candidates can drop their CV on aishwaryapawar@sevenmentor.com OR contact on 9503389804

Job Purpose Looking for exceptional Data Scientist with a proven track record of experience in Predictive analytics. Job Responsibilities(JR) : 6 8 Areas Actionable (4-6) Scorecard Building and Modelling Developing analytical models to assess risk profile of a customer / identifying cross-sell opportunities/fraud control for new and existing customers Responsible for development and deployment of various scorecards / models for the credit risk / Retail asset products of the Bank within the specified timelines. Ensure the deployment also is line with Bank’s strategies so as to gain maximum efficiencies. Estimate probability of default arising out of the scorecards and monitor deviation from expected default rates. Monitor portfolio and identify pockets of opportunity for business growth and risk alerts to control NPAs. Communicate these alerts to the respective owners and follow-up for closure Formulating data cuts and strategies to assess credit risk for new and existing customers of the Bank. Give feedback to stakeholders to improve the usage of the models Develop novel approaches/algorithms in Risk modeling to constantly improve the operational efficacy of current models and its impact to stake holders To adopt the latest trends wrt fintech companies by applying the best-in-class financial models, risk strategies To work on various aspects related to automation of scorecards in Analytics domain. Explore data available within the Banks ecosystem but not used currently to meet the above stated business objectives Innovation Thinking, evolving and making significant changes in the processes, techniques, methods so as to save time, energy and money. Any other assignments depending on the needs of the organization Educational Qualifications Key Skills 1. MCA/MTech/MSc Statistics or Economics/BTech/MBA or equivalent in Computer science/Statistics or related areas with strong inclination towards machine learning algorithms is preferred Excellent problem solving capabilities with strong fundamentals in computer science Strong technical & analytical skills Hands-on experience in data wrangling (ETL), feature engineering, building and deploying scalable machine learning algorithms Strong written and verbal communication skills Excellent knowledge of current trends in the field of machine learning/analytics field Experience Required Experience of 2+ years in analytics/predictive modeling/machine learning Experience of 2+ years in Python/R in building as well as deploying scalable analytics based models Exposure to banking preferable Major Stakeholders (intra team and cross functional stakeholders, who would need to be interacted with for discharging duties) Credit Policy Underwriting Process Fraud Control Product Credit Bureaus Third Party Analytics Service Providers IT Legal Information Security

Data Science Senior Advisor Data Science is all about breaking new ground to enable businesses to answer their most urgent questions. Pioneering massively parallel data-intensive analytic processing, our mission is to develop a whole new approach to generating meaning and value from petabyte-scale data sets and shape brand new methodologies, tools, statistical methods and models. Whats more, we are in collaboration with leading academics, industry experts and highly skilled engineers to equip our customers to generate sophisticated new insights from the biggest of big data. Join us to do the best work of your career and make a profound social impact as a Data Science Senior Advisor on our Pricing Analytics Team under Client Solutions Group located in Bangalore . What youll achieve As a Data Science Senior Advisor, you will be responsible for contributing to business strategy and influence decision making based on information gained from deep dive analysis. You will produce actionable and compelling recommendations by interpreting insights from complex data sets. You will design processes to consolidate and examine unstructured data to generate actionable insights. You will also partner with business leaders, engineers and industry experts to construct predictive models, algorithms and probability engines. You will: •Collaborate with internal and external teams to understand customer requirements •Develop and apply a broad range of techniques and theories from statistics, machine learning, and business intelligence to deliver actionable business insights •Develop and drive testing of algorithms efficacy for differing analytical use-cases •Performs end-to-end steps involved in model development while establishing subject-matter expertise •Work with the academic and business community to develop new techniques and to contribute to research in the area of large databases Take the first step towards your dream career Every Dell Technologies team member brings something unique to the table. Here’s what we are looking for with this role: Essential Requirements •8 to 12 years of related experience •Solid statistical skills. ML exp, LLM models •Solid Python Programming •Good understanding of business environment and industry trends •Good communication and problem-solving skills and being customer focused Desirable Requirements •Bachelor’s degree •Ability to act as a coach to the team •Strong product/technology/industry knowledge

Job Title: Data Scientist Experience: 5+ years Location: Ambattur Estate, Chennai Work Type : Work from office (no hybrid or remote) Email to Apply: jerlinbetsy.m@accesshealthcare.com About the Role: Access Healthcare is looking for a talented and driven Data Scientist to turn complex data into actionable business insights. If you have strong technical expertise, a knack for problem-solving, and the ability to communicate stories through data, this is your opportunity to make a real business impact. Eligibility Criteria : 5+ years of experience, with a track record of solving complex business problems using data. Certifications in Data Science, Machine Learning, or AI platforms ( preferred) Competency Requirement (Technical & Behavioral): Proficiency in Python or R for data analysis and model building. Strong knowledge of SQL for data extraction and manipulation. Experience with machine learning algorithms (regression, classification, clustering, etc.) Familiarity with data visualization tools like Tableau, Power BI Strong analytical and problem-solving skills Excellent communication and storytelling abilities to present complex data in a clear and concise manner Ability to work both independently and collaboratively in cross-functional teams Capacity to handle change, stay open to different ideas, support positive changes. Very high in Integrity and should be attentive to detail. Should be self- motivated and agile Should be able to influence and inspire Teams at all levels of the organization Roles & Responsibilities: Work closely with business, product, BEX & SQ teams to understand requirements Gather structured and unstructured data from multiple sources Clean and transform data to ensure quality and consistency Perform statistical analysis to identify trends, correlations, and anomalies. Use visualization tools to communicate data patterns and insights Design, build, and validate predictive models wherever required Select appropriate techniques based on problem type for ex regression Translate complex data findings into actionable business insights Develop reports, and visualizations to communicate results effectively to non-technical stakeholders Design and run experiments to test hypotheses and measure the impact of business decisions. Analyze test results and suggest next steps or optimizations. Stay updated with the latest trends, tools, and technologies in data science and machine learning. Contact ID - jerlinbetsy.m@accesshealthcare.com

Experience in CI/CD pipelines, scripting languages, and a deep understanding of version control systems (e.g. Git), containerization (e.g. Docker), and continuous integration/deployment tools (e.g. Jenkins) third party integration is a plus, cloud computing platforms (e.g. AWS, GCP, Azure), Kubernetes and Kafka. Experience in 4+ years of experience building production-grade ML pipelines. Proficient in Python and frameworks like Tensorflow, Keras, or PyTorch. Experience with cloud build, deployment, and orchestration tools Experience with MLOps tools such as MLFlow, Kubeflow, Weights & Biases, AWS Sagemaker, Vertex AI, DVC, Airflow, Prefect, etc., Experience in statistical modeling, machine learning, data mining, and unstructured data analytics. Understanding of ML Lifecycle, MLOps & Hands on experience to Productionize the ML Model Detail-oriented, with the ability to work both independently and collaboratively. Ability to work successfully with multi-functional teams, principals, and architects, across organizational boundaries and geographies. Equal comfort driving low-level technical implementation and high-level architecture evolution Experience working with data engineering pipelines.

Bachelor's /Master's /PhD degree in a quantitative field (CS, Machine learning, Mathematics, Economics, Statistics, Data Science) Preferred Institution: NIT, ISI, Any - School of Economics Responsibilities: Serve as expert in Data Science, build framework to develop Production level DS/AI models. Apply AI research and ML models to accelerate business innovation and solve impactful business problems for our clients. Partner with business and technical stakeholders to translate challenging business problems into state-of-the-art data science solutions. Present results, insights, and recommendations to senior management with an emphasis on the business impact. Build engaging rapport with client leadership through relevant conversations and genuine business recommendations that impact the growth and profitability of the organization. Required Skills: Expertise in ML - Regression, Classification, Clustering, Time Series Modeling, Graph Network, Recommender System, Bayesian modeling, Deep learning, Computer Vision, NLP/NLU, Reinforcement learning, Federated Learning, Meta Learning. Proficient in some or all of the following techniques: Linear & Logistic Regression, Decision Trees, Random Forests, K-Nearest Neighbors, Support Vector Machines ANOVA, Principal Component Analysis, Gradient Boosted Trees, ANN, CNN, RNN, Transformers. Expertise in programming languages SQL, Python/ R, Spark. Expertise in ML frameworks and libraries (TensorFlow, Keras, PyTorch). Experience with cloud computing services Azure. Expert in Statistical Modelling & Algorithms E.g. Hypothesis testing, Sample size estimation, A/B testing. Knowledge in Mathematical programming - Linear Programming, Mixed Integer Programming etc , Stochastic Modelling - Markov chains, Monte Carlo, Stochastic Simulation, Queuing Models. Experience with Optimization Solvers (Gurobi, Cplex) and Algebraic programming Languages(PulP). Knowledge in GPU code optimization, Spark MLlib Optimization. Familiarity to deploy and monitor ML models in production, delivering data products to end-users. Experience with ML CI/CD pipelines.

About the Role As a Principal Data Scientist in our AdTech team, youll drive innovation in our advertising platform using advanced machine learning and statistical methods. Youll tackle complex problems in real-time bidding, ad ranking optimization, budget efficiency, and performance measurement that directly impact our businesss bottom line. This role requires technical excellence and business acumen and youll collaborate with cross-functional teams to transform data insights into actionable strategies that enhance our advertising ecosystem. What you will do Design and develop sophisticated bidding, budget pacing and other algorithms that optimize ad spend or ROI. Create frameworks and experimental design to measure ad effectiveness and ROI. Collaborate with product and engineering teams to translate business requirements into efficient AI/ML solutions. Communicate long-term roadmap, insights and recommendations to tech and business leadership. Mentor junior data scientists and provide technical Lead research initiatives in machine learning, auction theory and advertising technology. What you will need B.Tech in Computer Science, Machine Learning, or a related field with at least 6+ years of experience in AI/ML research. Experience in auction theory, predictive modelling, causal inference, and reinforcement learning. Expertise in PyTorch or TensorFlow, and proficiency in Python as well as big data technologies. History of mentoring junior data scientists, and comfortable in driving multiple problem statements. Excellent communication skills, able to explain complex concepts to both technical and non-technical audiences. Preferred Qualifications: M.Tech or Ph.d in Computer Science with a specialization in Machine Learning. 3+ years of experience applying machine learning and statistical modeling in AdTech, or related domains. Exposure in real-time bidding systems, programmatic advertising, or ad exchanges. Track record of successful research-to-product transitions. Strong publication record in top AI conferences (e.g., NeurIPS, ICML, ICLR, KDD, CVPR, AAAI).

JOIN US AS A LEAD SYSTEMS ANALYST About the company: As a Fortune 50 company with more than 400,000 team members worldwide, Target is an iconic brand and one of America's leading retailers. Joining Target means promoting a culture of mutual care and respect and striving to make the most meaningful and positive impact. Becoming a Target team member means joining a community that values different voices and lifts each other up . Here, we believe your unique perspective is important, and you'll build relationships by being authentic and respectful. Overview about TII At Target, we have a timeless purpose and a proven strategy. And that hasnt happened by accident. Some of the best minds from different backgrounds come together at Target to redefine retail in an inclusive learning environment that values people and delivers world-class outcomes. That winning formula is especially apparent in Bengaluru, where Target in India operates as a fully integrated part of Targets global team and has more than 4,000 team members supporting the companys global strategy and operations. PRIMARY FUNCTION: At Target in India, our Tax Technology team plays a crucial role in enabling efficient and accurate compliance with US Sales and Use Tax (SUT) regulations. By collaborating closely with the Tax, Product and Tech teams in the US, this team leverages innovative technologies and advanced analytics to enhance operational efficiency and support seamless tax compliance processes. As a Lead Systems Analyst, you will own the compliance data integration, transformation, and load processes, ensuring accuracy, efficiency and seamless operations. You will provide strategic oversight of tax systems, proactively identify improvement opportunities and partner closely with cross-functional teams to enhance automation and analytics capabilities. In addition to SUT, this role will explore opportunities to support income and property tax technology needs. Your leadership in evaluating processes, defining technology-driven solutions and driving execution will be key to optimizing tax operations. This role will also focus on the below areas Lead and oversee the data integration and compliance load processes, ensuring flawless execution, accuracy and efficiency while proactively driving solutions and driving continuous improvements. Drive transparency through documentation and reporting of compliance related issues, identifying trends and working with management to implement corrective actions and long-term enhancements. Act as a strategic partner between Tax, Product and Tech teams to address queries, provide analysis and resolve challenges related to compliance load process, workflows, Vertex returns, SSAS etc. Drive the configuration, testing and validation of tax system updates and integrations to ensure seamless operation and compliance. Establish and enforce data quality controls, ensuring the integrity, accuracy and completeness of tax related data through rigorous analysis, reconciliation and validation. Design and implement Alteryx workflows, leverage tools / language such as SSAS, SQL etc. to streamline tax processes and improve analytics capabilities. Apply innovative solutions including generative AI, machine learning and RPA to automate repetitive tasks and enhance accuracy in tax reporting. Continuously look for opportunities to improve, automate and enhance existing processes for efficiency. Collect and organize required data for audit requests ensuring accurate and timely submissions. Respond to requests for reporting and data from tax users to support sales, income, and property tax compliance and analytics needs. Working within Tax, your mission will be to drive value-added work and support our core retail business goals. Our tax team focuses on all aspects of tax reporting including enhancing productivity and efficiency of core compliance through process and technology, monitoring tax risk and opportunities across all tax disciplines, engaging and educating Finance and the broader organization regarding tax considerations, and prioritizing team resources to support key work streams. 8+ years of experience in tax technology or systems analysis, preferably within a large corporate tax department or consulting firm, with a focus on SUT compliance. Bachelors or Masters degree in Taxation, Finance or Information Systems or an equivalent combination of professional education and experience. Proficiency with tax technology tools and applications including Vertex O-Series, Vertex Returns, Alteryx, SQL and RPA with experience in using these tools to streamline tax compliance, automate workflows and enhance data accuracy and reporting. Experience working on ERP systems (e.g. SAP) and data visualization tools like Tableau or Power BI. Proven ability to collaborate with cross-functional teams, acting as a liaison between Tax, Tech and Product teams to resolve queries and enhance processes. Familiarity with machine learning, generative AI and statistical modeling is a plus. Prior experience of working for a retail organization is strongly preferred. Excellent communication and strong interpersonal skills, as well as the ability to work independently with limited direction and guidance A proactive mindset and keen analytical ability, attention to detail, and the ability to meet tight deadlines.

Job Role: Data scientists will develop and maintain statistical models, apply machine learning techniques and build high-quality predictive/prescriptive systems. The Sr data scientist will also make technology and business recommendations, as well as develop key insights based on data analysis. The candidate must be able to partner with business stakeholders in order to cure business problem statements and guide which business priorities using data. About NAM NAM Info Inc. a talent management organization specializes in IT Services delivery and Product development. Job Title: Data Scientist / Lead Data Scientist Company: NAM Info Private Limited Location: Bangalore (Work from Office all 5days a week) Experience: 8-12 Years Positions: 2 Data Scientists & 1 Lead Data Scientist Joining: Immediate joiners preferred (within 15 days) Interview Process: Round 1: Virtual Round 2: Face-to-face Academic Qualifications: Engineering / B Tech or Masters in Computer SCience Responsibilities: Strong knowledge and hands on experience in exploration data analysis (EDA) Require reasonable exposure to Retail domain. 2+yrs of experience in ML Model Experience where the candidate has built and deployed Machine learning models at scale Must have Comfortable in Python (Coding) and build the model understanding concept Experience in feature engineering: Experience in building derived variable and hyperparameter tuning Types of models experience expected: Classification models, Regression models, Clustering, Forecasting (Experience in Machine Learning and Deep Learning Techniques) Experience with Hadoop, Apache Spark, Kafka, and cloud platforms (AWS, GCP, Azure). Proficient with EC2, S3, RDS, Lambda, Snowflake, and big data technologies. Data Visualization and BI Tools: Created interactive dashboards and reports using Tableau, Power BI, and D3.js to facilitate data-driven decision-making. Must have worked on banking use cases like cross sell, upsell, customer retention, customer acquisition, customer servicing, personalization, ATM optimization, Branch analytics Expertise in data science mining and Time Series, modeling, deep learning, CNN, clustering, boosting, classification, predictive modeling, LSTM, and LLMs. Note: Apply only if you meet the Expectation criteria which mentioned in the Job Description. Send profiles to narasimha@nam-it.com Thanks & regards, Narasimha.B Staffing executive NAM Info Pvt Ltd, 29/2B-01, 1st Floor, K.R. Road, Banashankari 2nd Stage, Bangalore - 560070. +91 9182480146 (India) Email - narasimha@nam-it.com

Greetings from Access Healthcare Services, We have an excellent opportunity for an Data Scientist. Shifts : General Job Location : Ambattur Estate, Chennai Eligibility Criteria : Bachelors / masters degree in computer science, Data Science, Statistics, Mathematics, Engineering, or a related quantitative field 5 to 10 years of experience, with a proven track record of solving complex business problems using data. Certifications in Data Science, Machine Learning, or AI platforms ( preferred) Competency Requirement (Technical & Behavioral): Proficiency in Python or R for data analysis and model building. Strong knowledge of SQL for data extraction and manipulation. Experience with machine learning algorithms (regression, classification, clustering, etc.) Familiarity with data visualization tools like Tableau, Power BI Strong analytical and problem-solving skills Excellent communication and storytelling abilities to present complex data in a clear and concise manner Ability to work both independently and collaboratively in cross-functional teams Capacity to handle change, stay open to different ideas, support positive changes. Very high in Integrity and should be attentive to detail. Should be self- motivated and agile Should be able to influence and inspire Teams at all levels of the organization Roles & Responsibilities: Work closely with business, product, BEX & SQ teams to understand requirements Gather structured and unstructured data from multiple sources Clean and transform data to ensure quality and consistency Perform statistical analysis to identify trends, correlations, and anomalies. Use visualization tools to communicate data patterns and insights Design, build, and validate predictive models wherever required Select appropriate techniques based on problem type for ex regression Translate complex data findings into actionable business insights Develop reports, and visualizations to communicate results effectively to non- technical stakeholders Design and run experiments to test hypotheses and measure the impact of business decisions. Analyze test results and suggest next steps or optimizations. Stay updated with the latest trends, tools, and technologies in data science and machine learning. Interested candidates, Please share your resume to nandhinik.outsource@accesshealthcare.com Note: - Please share the above requirement with your friends.

Job Summary: Enable data driven decision making across the Tesco business globally by developing analytics solutions using a combination of math, tech and business knowledge Roles and Responsibilities: - Identifying operational improvements and finding solutions by applying CI tools and techniques - Responsible for completing tasks and transactions within agreed KPI's - Knows and applies fundamental work theories/concepts/processes in own areas of work Engaging with business & functional partners to understand business priorities, ask relevant questions and scope same into a analytical solution document calling out how application of data science will improve decision making - In depth understanding of techniques to prepare the analytical data set leveraging multiple complex data set sources - Building Statistical models and ML algorithms with practitioner level competency - Writing structured, modularized & codified algorithms using Continuous Improvement principles (development of knowledge assets and reusable modules on GitHub, Wiki, etc.) with expert competency - Building easy visualization layer on top of the algorithms in order to empower end-users to take decisions - this could be on a visualization platform (Tableau / Python) or through a recommendation set through PPTs - Working with the line manager to ensure application / consumption and also think beyond the immediate ask and spot opportunities to address the bigger business questions (if any) Key people and teams I work with in and outside of Tesco: People, budgets and other resources I am accountable for in my job: Enterprise Analytics Senior Management Partners across the global Tesco business Experience relevant for this job: - Applied Math: Applied Statistics, Design of Experiments, Linear -1-2-year experience in data science application in Retail or CPG & Logistic Regression, Decision Trees, Forecasting, Optimization Preferred algorithms - Functional experience: Marketing, Supply Chain, Customer, - Tech: SQL, Hadoop, Python, Tableau, MS Excel, MS Merchandising, Operations, Finance or Digital PowerPoint - Soft Skills: Analytical Thinking & Problem solving, Storyboarding

Bachelor's /Master's /PhD degree in a quantitative field (CS, Machine learning, Mathematics, Economics, Statistics, Data Science) Preferred Institution: NIT, ISI, Any - Scool of Economics Responsibilities: Serve as expert in Data Science, build framework to develop Production level DS/AI models. Apply AI research and ML models to accelerate business innovation and solve impactful business problems for our clients. Partner with business and technical stakeholders to translate challenging business problems into state-of-the-art data science solutions. Present results, insights, and recommendations to senior management with an emphasis on the business impact. Build engaging rapport with client leadership through relevant conversations and genuine business recommendations that impact the growth and profitability of the organization. Required Skills: Expertise in ML - Regression, Classification, Clustering, Time Series Modeling, Graph Network, Recommender System, Bayesian modeling, Deep learning, Computer Vision, NLP/NLU, Reinforcement learning, Federated Learning, Meta Learning. Proficient in some or all of the following techniques: Linear & Logistic Regression, Decision Trees, Random Forests, K-Nearest Neighbors, Support Vector Machines ANOVA, Principal Component Analysis, Gradient Boosted Trees, ANN, CNN, RNN, Transformers. Expertise in programming languages SQL, Python/ R, Spark. Expertise in ML frameworks and libraries (TensorFlow, Keras, PyTorch). Experience with cloud computing services Azure. Expert in Statistical Modelling & Algorithms E.g. Hypothesis testing, Sample size estimation, A/B testing. Knowledge in Mathematical programming - Linear Programming, Mixed Integer Programming etc , Stochastic Modelling - Markov chains, Monte Carlo, Stochastic Simulation, Queuing Models. Experience with Optimization Solvers (Gurobi, Cplex) and Algebraic programming Languages(PulP). Knowledge in GPU code optimization, Spark MLlib Optimization. Familiarity to deploy and monitor ML models in production, delivering data products to end-users. Experience with ML CI/CD pipelines.

Role Purpose The purpose of the role is to define, architect and lead delivery of machine learning and AI solutions. Do 1. Demand generation through support in Solution development a. Support Go-To-Market strategy i. Contribute to development solutions, proof of concepts aligned to key offerings to enable solution led sales b. Collaborate with different colleges and institutes for research initiatives and provide data science courses 2. Revenue generation through Building & operationalizing Machine Learning, Deep Learning solutions a. Develop Machine Learning / Deep learning models for decision augmentation or for automation solutions b. Collaborate with ML Engineers, Data engineers and IT to evaluate ML deployment options 3. Team Management a. Talent Management i. Support on boarding and training to enhance capability & effectiveness Mandatory Skills: Data Science. Experience: 3-5 Years.

Bachelor's /Master's /PhD degree in a quantitative field (CS, Machine learning, Mathematics, Economics, Statistics, Data Science) Preferred Institution: NIT, ISI, Any - School of Economics Required Skills: Expertise in ML - Regression, Classification, Clustering, Time Series Modeling, Graph Network, Recommender System, Bayesian modeling, Deep learning, Computer Vision, NLP/NLU, Reinforcement learning, Federated Learning, Meta Learning. Proficient in some or all of the following techniques: Linear & Logistic Regression, Decision Trees, Random Forests, K-Nearest Neighbors, Support Vector Machines ANOVA, Principal Component Analysis, Gradient Boosted Trees, ANN, CNN, RNN, Transformers. Expertise in programming languages SQL, Python/ R, Spark. Expertise in ML frameworks and libraries (TensorFlow, Keras, PyTorch). Knowledge in cloud computing services Azure. Expert in Statistical Modelling & Algorithms E.g. Hypothesis testing, Sample size estimation, A/B testing. Knowledge in Mathematical programming - Linear Programming, Mixed Integer Programming etc , Stochastic Modelling - Markov chains, Monte Carlo, Stochastic Simulation, Queuing Models. Familiarity to deploy and monitor ML models in production, delivering data products to end-users.

Roles and Responsibilities Develop credit risk models using SAS, SQL, and statistical modeling techniques to predict defaults, losses, and other credit-related metrics. Collaborate with cross-functional teams to design and implement effective credit risk strategies that meet business objectives. Conduct stress testing and scenario analysis to identify potential risks and opportunities for growth. Provide data insights and recommendations to stakeholders on loss forecasting, scorecards, and portfolio performance. Desired Candidate Profile 2+ years of experience in Credit Risk Modelling/Analytics or related field. Strong expertise in Basel II/III regulations, CECL/CCAR requirements under IFRS9 framework. Proficiency in programming languages such as Python/R/SAS; strong understanding of machine learning algorithms an added advantage.

Role Purpose The purpose of the role is to define, architect and lead delivery of machine learning and AI solutions Do 1. Demand generation through support in Solution development a. Support Go-To-Market strategy i. Collaborate with sales, pre-sales &consulting team to assist in creating solutions and propositions for proactive demand generation ii. Contribute to development solutions, proof of concepts aligned to key offerings to enable solution led sales b. Collaborate with different colleges and institutes for recruitment, joint research initiatives and provide data science courses 2. Revenue generation through Building & operationalizing Machine Learning, Deep Learning solutions a. Develop Machine Learning / Deep learning models for decision augmentation or for automation solutions b. Collaborate with ML Engineers, Data engineers and IT to evaluate ML deployment options c. Integrate model performance management tools into the current business infrastructure 3. Team Management a. Resourcing i. Support recruitment process to on-board right resources for the team b. Talent Management i. Support on boarding and training for the team members to enhance capability & effectiveness ii. Manage team attrition c. Performance Management i. Conduct timely performance reviews and provide constructive feedback to own direct reports ii. Be a role model to team for five habits iii. Ensure that the Performance Nxt is followed for the entire team d. Employee Satisfaction and Engagement i. Lead and drive engagement initiatives for the team Mandatory Skills: Python for Data Science. Experience: 5-8 Years.

Over 10 years of experience with a continuous focus on data science throughout my career. Successfully deployed at least two production-grade Generative AI solutions, with hands-on exposure to Agentic AI frameworks. Expertise in Robotics including Multiagent Systems, Automated Planning & Scheduling, Intelligence, and Orchestration. Proficient in AI & ML , covering Supervised and Unsupervised Learning, Neural Networks, Large Language Models (LLMs), as well as Full-stack Software Engineering and System Design. Proven ability to apply emerging technologies to address complex business challenges. Technical proficiency includes Python, FastAPI, Ollama, RDBMS (PostgreSQL), Message Brokers, UI Frameworks (Angular, Streamlit), Robot Operating System (ROS), AI/ML Python frameworks (scikit-learn, PyTorch, etc.), AWS, Azure, and Git. Recognised expert in machine learning, Generative AI, LLMs, SLMS, and Agents, with a strong emphasis on computer vision, deep learning, and statistical modelling; led innovative projects in video analytics, face recognition, and retail analytics utilising tools such as OpenCV and Point Cloud Libraries. In-depth knowledge of robot kinematics, navigation, planning, multi-agent orchestration, neural networks, software engineering, architecture, OOP, and the Git ecosystem. Experienced in techno-functional product and project management, contributing to key research and business decisions. Skilled at interpreting research publications and staying updated with the latest technological advancements. Strong background in Computer Vision, AI, ML/DL, Generative AI, Large Language Models, and Agentic AI. Possess experience from product-based companies and an academic background from IIT. Mandatory Skills: Machine Learning.Experience: 8-10 Years.

We are looking for a skilled professional with 8 to 14 years of experience to join our team as an Assistant Manager - Analytics in Hyderabad. The ideal candidate will have a strong background in analytics and data management, with excellent problem-solving skills. Roles and Responsibility Develop and implement advanced analytics models to drive business growth and improvement. Collaborate with cross-functional teams to identify and prioritize business needs. Design and maintain large-scale databases and data systems for data-driven decision-making. Analyze complex data sets to extract insights and trends that inform business strategy. Develop and present reports and dashboards to senior management and stakeholders. Stay up-to-date with industry trends and emerging technologies in analytics and data management. Job Requirements Strong understanding of CRM/IT Enabled Services/BPO industry operations and challenges. Proven experience in managing large datasets and developing advanced analytics models. Excellent problem-solving skills and ability to work in a fast-paced environment. Strong communication and collaboration skills, with the ability to work with diverse teams. Ability to analyze complex data sets and extract meaningful insights. Experience with data visualization tools and reporting software.

The leader must demonstrate an ability to anticipate, understand, and act on evolving customer needs, both stated and unstated. Through this, he/she must create a customer-centric organization and use innovative thinking frameworks to foster value-added relations. Associate Program Manager Roles and responsibilities: Lead and provide strategic direction to teams, ensuring alignment with clients business objectives Actively collaborate with the Marketing, Marketing Operations, Marketing Technology, Risk & Controls, and Automation teams to consult and facilitate the seamless execution of marketing campaigns and initiatives Collaborate with client stakeholders to shape and execute the target operating model for data operations, data engineering, and insights teams Drive revenue growth by understanding client needs, proposing innovative commercial constructs, and capitalising on upsell & cross-sell opportunities Accountable for ensuring we are recruiting a highly skilled workforce of data engineers, data analysts and data scientists to support RTB and CTB initiatives of the Client Work closely with sales and consulting teams to expand current business and explore new transformation-led opportunities Stay updated with industry trends, and champion the adoption of cutting-edge tools, methodologies, and technologies Take ownership of team deliverables, ensuring quality checks, best practices and desired outcomes are achieved on the first attempt. Understand project requirements and equip team members with the necessary skills and training. Technical and Functional Skills: Masters / Bachelors degree in Management / Engineering / Mathematics / Statistics or any related quantitative discipline The ideal candidate must have a minimum of 8+ years of experience in Data Management, Analytics, or Decision Science, including P&L Management responsibilities Experience working in services/consulting space, building and leading large analytics business and demonstrated success in delivering to clients across industries and domains preferably Banking and Financial Services Proven track record of building and leading high growth teams; demonstrated experience in hiring, retaining, and scaling geographically dispersed, high-performing teams Experience in collaborating, communicating, and influencing different stakeholders to drive inclusion, efficiency, and creative solutions

Role Purpose The purpose of the role is to define, architect and lead delivery of machine learning and AI solutions Do 1. Demand generation through support in Solution development a. Support Go-To-Market strategy i. Collaborate with sales, pre-sales &consulting team to assist in creating solutions and propositions for proactive demand generation ii. Contribute to development solutions, proof of concepts aligned to key offerings to enable solution led sales b. Collaborate with different colleges and institutes for recruitment, joint research initiatives and provide data science courses 2. Revenue generation through Building & operationalizing Machine Learning, Deep Learning solutions a. Develop Machine Learning / Deep learning models for decision augmentation or for automation solutions b. Collaborate with ML Engineers, Data engineers and IT to evaluate ML deployment options c. Integrate model performance management tools into the current business infrastructure 3. Team Management a. Resourcing i. Support recruitment process to on-board right resources for the team b. Talent Management i. Support on boarding and training for the team members to enhance capability & effectiveness ii. Manage team attrition c. Performance Management i. Conduct timely performance reviews and provide constructive feedback to own direct reports ii. Be a role model to team for five habits iii. Ensure that the Performance Nxt is followed for the entire team d. Employee Satisfaction and Engagement i. Lead and drive engagement initiatives for the team Mandatory Skills: ML Ops.Experience: 5-8 Years.

Type : Internship Duration: 6 months Position Overview: We are seeking a Data Analyst - Return Experience to support analytics and insights for improving the return process and fraud reduction. The role involves working closely with cross-functional teams to monitor return metrics, identify fraud, inefficiencies, and provide actionable insights. The ideal candidate will have to be a self-starter, must have a strong analytical mindset, a passion for solving complex problems, and have the ability to work with large datasets with great ease Key Responsibilities:. Analyze data to identify inefficiencies in current workflows and recommend data-backed solutions. Regularly monitor, analyze and provide insights related to return metrics such as fraud, fraud rates, return speed, return rate, and customer feedback. Assist in identifying fraud patterns and inefficiencies within the return supply chain. Create visual dashboards and reports for easy consumption by stakeholders. Monitor return speed and identify areas for quality improvement in reverse logistics. Track key OKRs impacting seller experience and provide actionable insights to stakeholders. Support automation of reports and dashboards to streamline data reporting processes. Provide data insights to help stakeholders improve return operations and fraud prevention processes. Qualifications: Bachelor s degree in a relevant field (e.g., Data Analytics, Statistics, Mathematics, Computer Science). 0-2 years of experience in data analytics or a related field. Proficiency in SQL, Python and Microsoft excel Basic understanding of Python or R for data analysis (preferred but not mandatory). Strong analytical and problem-solving skills, with attention to detail. Good communication skills and the ability to collaborate with cross-functional teams. Eagerness to learn and grow in a fast-paced, data-driven environment.

The candidate must possess knowledge relevant to the functional area, and act as a subject matter expert in providing advice in the area of expertise, and also focus on continuous improvement for maximum efficiency. It is vital to focus on the high standard of delivery excellence, provide top-notch service quality and develop successful long-term business partnerships with internal/external customers by identifying and fulfilling customer needs. He/she should be able to break down complex problems into logical and manageable parts in a systematic way, and generate and compare multiple options, and set priorities to resolve problems. The ideal candidate must be proactive, and go beyond expectations to achieve job results and create new opportunities. He/she must positively influence the team, motivate high performance, promote a friendly climate, give constructive feedback, provide development opportunities, and manage career aspirations of direct reports. Communication skills are key here, to explain organizational objectives, assignments, and the big picture to the team, and to articulate team vision and clear objectives. Job Description: We are looking for a skilled Modeling Analytics Specialist to join our dynamic team. In this role, you will be responsible for leveraging advanced statistical and machine learning models to analyze complex data sets. Your insights and recommendations will drive strategic decision-making and optimize business processes. Senior Process Manager Roles and responsibilities: Develop and implement predictive models, segmentation analysis, and statistical analyses to extract insights from large datasets. Apply machine learning algorithms to solve business problems and improve operational efficiency. Collaborate with cross-functional teams to identify business requirements and translate them into analytical solutions. Utilize tools such as [list specific tools, e.g., Python, R] for data manipulation, modeling, and visualization. Create and automate reports and dashboards to present findings and actionable recommendations to stakeholders. Conduct deep dives into data to identify trends, patterns, and anomalies that can inform strategic initiatives. Ensure data accuracy and integrity by validating data sources and implementing quality assurance measures. Stay updated on industry trends and best practices in modeling, analytics, and data science. Technical and Functional Skills: Bachelors degree in Statistics, Mathematics, Computer Science, or a related field (preferred) with 7+ years of proven experience in statistical modeling, machine learning, and data analysis. Proficiency in programming languages such as [specific tools you use, e.g., Python, R]. Experience with data visualization tools (e.g., Tableau, Power BI) for presenting insights and findings. Strong analytical and problem-solving skills with the ability to interpret complex data sets. Excellent communication and collaboration skills to work effectively with diverse teams.

We are looking for a Senior Data Scientist who is passionate about solving complex business problems using data. The ideal candidate will have strong hands-on experience in Python , SQL , and advanced machine learning algorithms , along with domain expertise in forecasting , pricing optimization , or inventory planning . You will work closely with cross-functional teams including product, engineering, and business stakeholders to drive data-driven strategies. Key Responsibilities: Design, build, and deploy predictive and optimization models for use cases such as demand forecasting , dynamic pricing , or inventory optimization . Translate business problems into analytical frameworks and provide actionable insights. Build and maintain scalable data pipelines and model workflows using Python and SQL. Collaborate with data engineers to ensure model integration into production systems. Present findings and recommendations to leadership using data visualizations and storytelling. Stay current with the latest techniques in machine learning , statistics , and operations research . Lead and mentor junior data scientists and analysts when required. Required Skills and Experience: 5+ years of experience in a Data Science or Analytics role with a strong business impact. Strong programming skills in Python (pandas, scikit-learn, statsmodels, etc.). Proficiency in SQL for data extraction, transformation, and manipulation. Deep understanding of machine learning algorithms (regression, classification, clustering, time series forecasting). Experience with one or more of the following domains: Demand Forecasting Price Optimization Inventory Optimization / Supply Chain Analytics Strong problem-solving and quantitative skills. Experience working with large datasets and distributed computing tools (e.g., Spark, Hadoop) is a plus. Familiarity with data visualization tools (e.g., Tableau, Power BI, matplotlib, seaborn). Preferred Qualifications: Masters or PhD in Computer Science, Statistics, Mathematics, Economics, Operations Research, or a related field. Experience in retail, e-commerce, manufacturing, or logistics is a strong plus. Exposure to optimization libraries (e.g., PuLP, OR-Tools, Gurobi) is a bonus. Experience deploying models using MLOps tools or platforms is a plus.