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IDFC FIRST Bank

Senior Data Scientist

IDFC FIRST Bank Mumbai, Maharashtra, India

Banking · 10,001+ employees

Yesterday
data-scientist Senior (5-10 yrs) Full-time India
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About the role

The Senior Data Scientist will identify business needs to develop analytical tools and AI/ML models that drive strategic decision-making. They will also collaborate with data engineering teams to ensure high-quality data flow and validate models for accuracy and regulatory compliance.

What they look for

Data Science AI/ML Modeling Data Analytics Recommendation Engines Propensity Modeling Customer Segmentation Risk Modelling Data Cleansing Data Transformation Statistical Analysis Test Strategy Development Performance Validation Stakeholder Management Strategic Thinking Problem-solving Communication

Requirements

Candidates must hold a Bachelor's or Master's degree in a relevant field such as Computer Science, Statistics, or Economics. A minimum of 4 to 10 years of professional experience in data science or analytics is required.

Full description

Job Requirements About the Role

As a Senior Data Scientist in the Data & Analytics department, you will be responsible for identifying business needs and translating them into analytical tools and methods that drive strategic decision-making. You will work across teams to design data structures, implement test strategies, and ensure delivery of data analytics solutions aligned with business objectives. This role demands a strong foundation in data science, emerging technologies, and a proactive approach to innovation and problem-solving.

Key Responsibilities

Primary Responsibilities

  • Identify and scope business requirements and priorities through rigorous analysis and clarification of solutions, initiatives, and programs.
  • Monitor and integrate emerging technology trends and developments to identify new data products, services, and techniques.
  • Research, identify, and adopt best-in-class techniques in AI/ML modeling.
  • Apply advanced AI/ML techniques to solve problems related to customer segmentation, risk modelling, campaign targeting, and more.
  • Perform data cleansing, merging, enrichment, and transformation to prepare high-quality datasets for modelling.
  • Analyze large datasets to identify trends, patterns, and opportunities for business growth.
  • Build recommendation engines and propensity models to support cross-sell and up-sell strategies
  • Validate models to ensure accuracy, stability, and compliance with regulatory guidelines.
  • Present complex model outputs and insights in a clear, business-friendly manner.
  • Ensure traceability and version control of datasets, models, and evaluation pipelines.
  • Develop test strategies and systematic validation procedures to ensure models meet design specifications and performance standards.
  • Maintain a strong understanding of data structures and fields required for analysis and modelling.
  • Coordinate with the Data Engineering team to ensure data quality and seamless data flow.
  • Manage stakeholder expectations by aligning analytics outcomes with organizational objectives
  • Identify and evaluate digitization and innovation opportunities enabled by advancements in data and analytics.
  • Develop, select, and apply analytical tools and advanced computational methods to enable systems to learn, adapt, and deliver desired outcomes.

What We Are Looking For

Education

  • Graduation: B.Sc (Bachelor of Science) or B.Tech (Bachelor of Technology) or BCA (Bachelor of Computer Applications)
  • Post-Graduation: M.Sc (Master of Science) or M.Tech (Master of Technology), or MCA (Master of Computer Applications) or MA (Economics/Statistics)

Experience

  • 4 to 10 years of relevant experience in data analytics, data science, or related fields.

Skills and Attributes

  • Strong analytical and problem-solving skills.
  • Experience with designing and implementing scalable data structures and analytics solutions.
  • Familiarity with emerging technologies and data science tools.
  • Proficiency in test strategy development and performance validation.
  • Ability to manage stakeholder relationships and deliver data-driven insights.
  • Strategic thinking with a focus on innovation and business impact.
  • Excellent communication and collaboration skills.

Key Success Metrics

  • Development and deployment of analytical tools.
  • Delivery of business use cases through data analytics solutions.

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