IDFC FIRST Bank

Senior Data Scientist

IDFC FIRST Bank Bengaluru, Karnataka, India

Banking · 10,001+ employees

19 h ago
data-scientist Senior (5-10 yrs) Full-time India
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About the role

The Senior Data Scientist will identify business needs and translate them into analytical tools and methods to drive strategic decision-making. They will also design data structures, implement test strategies, and apply advanced AI/ML techniques to solve complex business problems.

What they look for

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

Requirements

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