Sr. Manager- II - BIU SC

ICICI Prudential Life Insurance Co.; Mumbai; On-site; INR 900,000 - 1,500,000; Full time

Job summary

ICICI Prudential Life Insurance Co. is seeking a skilled Data Scientist to design, develop, and deploy AI/ML solutions that solve real-world business problems. The role requires hands-on model development, analytics, dashboarding, and collaboration with cross-functional stakeholders.

You will work on GenAI applications, MLOps, data visualization, and end-to-end model lifecycle, driving scalable AI-driven outcomes that impact insurance product analytics and decision-making.

Qualifications

• Experience 1–2 years in Data Science, ML, or AI solution development with demonstrated project delivery experience.
• Education Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or related quantitative fields.
• ProgrammingLanguages Deep proficiency in Python and SQL is essential.
• ML/ AI expertise Hands-on experience with ML libraries and frameworks such as Scikit-learn, XGBoost, TensorFlow, PyTorch, or similar tools.
• Generative AI Exposure Experience working with LLMs, prompt engineering, vector databases, or GenAI frameworks is preferred
• Data Visualization Experience with dashboarding and visualization tools such as Power BI, Tableau, or similar platforms.
• Development Tools Familiarity with VS Code, Git, notebooks, APIs, and collaborative development workflows.
• MLOps & Deployment Basic understanding of MLOps concepts, CI/CD pipelines, model monitoring, and cloud-based AI deployments. Exposure to cloud platforms such as AWS, Azure, or GCP will be an advantage
• Preferred Experience in production deployment of ML/AI solutions, experience integrating AI solutions with APIs and enterprise systems, understanding of business problem solving using analytics and AI

Responsibilities

• ML/AI Solution Development Develop, train, evaluate, and deploy machine learning and AI models for business use cases including prediction, optimization, automation, and analytics.
• GenAI & LLM Applications Work on Generative AI use cases involving LLMs, prompt engineering, RAG-based solutions, AI copilots, and workflow automations
• Data Analysis & Visualization Perform exploratory data analysis, generate actionable insights, and create dashboards/reports using visualization tools to support business decision-making
• End-to-End Model Lifecycle Manage the ML lifecycle including data preparation, feature engineering, model development, validation, deployment, and monitoring
• Stakeholder Collaboration Partner with business stakeholders, product teams, and technology teams to understand requirements and translate them into scalable analytical and AI solutions
• MLOps & Deployment Support model deployment and monitoring using MLOps practices and tools. Collaborate with engineering teams for integration into production systems.
• Continuous Improvement & Innovation Stay updated with advancements in AI/ML, GenAI, and analytics ecosystems, and identify opportunities to improve existing solutions and processes.

Skills

Data Science

Machine Learning

Analytics

Problem Solving

Communication

Education

Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, Mathematics, Statistics

Tools

Python

SQL

Scikit-learn

XGBoost

TensorFlow

PyTorch

Power BI

Tableau

VS Code

Git

Notebooks

APIs

Job description

We are seeking a skilled and business-oriented Data Scientist to design,develop, and deploy AI/ML solutions that solve real-world business problems.The ideal candidate will have hands-on experience in machine learning modeldevelopment, analytics, dashboarding, and emerging GenAI capabilities, alongwith the ability to collaborate effectively with cross-functional stakeholders.The role requires a balance of technical expertise, problem-solving ability,and communication skills to deliver scalable and impactful AI-driven solutions.

KeyResponsibilities

• ML/AI SolutionDevelopment Develop, train, evaluate, and deploy machine learning and AImodels for business use cases including prediction, optimization,automation, and analytics.
• GenAI & LLMApplications Work on Generative AI use cases involving LLMs, promptengineering, RAG-based solutions, AI copilots, and workflow automations
• DataAnalysis & Visualization Perform exploratory data analysis, generateactionable insights, and create dashboards/reports using visualizationtools to support business decision-making
• End-to-EndModel Lifecycle Manage the ML lifecycle including data preparation,feature engineering, model development, validation, deployment, andmonitoring
• StakeholderCollaboration Partner with business stakeholders, product teams, andtechnology teams to understand requirements and translate them intoscalable analytical and AI solutions
• MLOps& Deployment Support model deployment and monitoring using MLOpspractices and tools. Collaborate with engineering teams for integrationinto production systems.
• ContinuousImprovement & Innovation Stay updated with advancements in AI/ML,GenAI, and analytics ecosystems, and identify opportunities to improveexisting solutions and processes.

RequiredQualifications and Skills

• Experience Minimum 1–2years of hands-on experience in Data Science, Machine Learning, or AIsolution development with demonstrated project delivery experience.
• Education Bachelor’sor Master’s degree in Computer Science, Data Science, Engineering,Mathematics, Statistics, or related quantitative fields.
• ProgrammingLanguages Deep proficiency in Python and SQL is essential.
• ML/ AI expertise Hands-onexperience with machine learning libraries and frameworks such asScikit-learn, XGBoost, TensorFlow, PyTorch, or similar tools.
• Generative AI Exposure Experienceworking with LLMs, prompt engineering, vector databases, or GenAIframeworks is preferred
• Data Visualization Experiencewith dashboarding and visualization tools such as Power BI, Tableau, orsimilar platforms.
• Development Tools Familiaritywith VS Code, Git, notebooks, APIs, and collaborative developmentworkflows.
• MLOps & Deployment Basicunderstanding of MLOps concepts, CI/CD pipelines, model monitoring, andcloud-based AI deployments. Exposure to cloud platforms such as AWS,Azure, or GCP will be an advantage
• Preferred Experiencein production deployment of ML/AI solutions, experience integrating AIsolutions with APIs and enterprise systems, understanding of businessproblem solving using analytics and AI