Sr. Manager- II - BIU SC

ICICI Prudential Life Insurance; Mumbai; On-site; INR 800,000 - 1,800,000; Full time

Job summary

ICICI Prudential Life Insurance seeks a skilled Data Scientist to design, develop, and deploy AI/ML solutions addressing real-world business problems. The role emphasizes collaboration with cross-functional teams to deliver scalable AI-driven outcomes.

The ideal candidate has hands-on experience in model development, analytics, dashboards, and GenAI capabilities, with strong communication to translate complex insights into business impact.

Qualifications

• Experience: 1–2 years in DS/ML solution development with project delivery.
• Education: Bachelor’s or Master’s in CS/DS/Engineering/Math/Stats or related field.
• Programming: Python and SQL essential.
• ML/AI: Hands-on with common libraries (scikit-learn, XGBoost, TensorFlow, PyTorch).

Responsibilities

• ML/AI Solution Development: train, evaluate, and deploy models for business use cases.
• GenAI & LLM Applications: work on Generative AI use cases, prompt engineering, RAG-based solutions.
• Data Analysis & Visualization: perform EDA, generate insights, and create dashboards/reports.
• End-to-End Model Lifecycle: manage data prep, feature engineering, validation, deployment, and monitoring.
• Stakeholder Collaboration: partner with business, product, and tech teams to translate requirements.
• MLOps & Deployment: support deployment and monitoring; collaborate for production integration.
• Continuous Improvement & Innovation: stay updated with AI/ML advances and opportunities.

Skills

Problem solving

Communication

Education

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

Tools

Python

SQL

Scikit-learn

XGBoost

TensorFlow

PyTorch

Power BI

Tableau

VS Code

Git

APIs

AWS

Azure

GCP

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, or similar platforms.
• Development Tools Familiaritywith VS Code, Git, notebooks, APIs, and collaborative developmentworkflows.
• MLOps & Deployment Basicunderstanding 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 Experiencein production deployment of ML/AI solutions, experience integrating AIsolutions with APIs and enterprise systems, understanding of businessproblem solving using analytics and AI