Sr. Manager- I - BIU - Customer Analytics SC

ICICI Prudential Life Insurance; Mumbai; On-site; INR 1,500,000 - 2,100,000; Full time

Job summary

ICICI Prudential Life Insurance is seeking a data-driven Sr. Manager- I in BIU to design, develop, and deploy AI/ML solutions that address real-world business needs. The role emphasizes collaboration with cross-functional teams to deliver scalable analytics and GenAI-enabled outcomes.

The ideal candidate has hands-on ML experience, strong data visualization skills, and the ability to communicate complex insights to stakeholders. Experience with GenAI and dashboards is highly valued.

Qualifications

• 1–2 years of hands-on Data Science/AI solution development experience.
• Bachelor’s or Master’s degree in a quantitative field.

Responsibilities

• Develop, train, evaluate, and deploy ML/AI models for business use cases.
• Work on GenerativeAI use cases involving LLMs and prompt engineering.
• Create dashboards/reports to support business decisions.
• Manage ML lifecycle from data prep to deployment and monitoring.
• Collaborate with stakeholders to translate requirements into AI solutions.
• Support model deployment and monitoring, including production integration.

Skills

Python

SQL

Machine Learning

Data Visualization

Education

Bachelor’s or Master’s degree in Computer Science

Tools

Scikit-learn

XGBoost

TensorFlow

PyTorch

Job description

Sr. Manager- I - BIU - Customer Analytics SC

Job Description- AI/ML Developer Job Description (BIU)

Experience Level 1 to 2 Years

Job Overview

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 model development, analytics, dashboarding, and emerging GenAI capabilities, along with 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.

Key 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 GenerativeAI 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.

Required Qualifications and Skills

• Experience Minimum 1–2 years of hands-on experience in Data Science, Machine Learning, 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.
• Programming Languages Deep proficiency in Python and SQL is essential.
• ML/ AI expertise Hands-on experience with machine learning 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