Data Science Manager

ICICI Securities
Navi Mumbai, Maharashtra, India

Department: Data Science Unit

Key Responsibilities

  • Design, develop, and deploy statistical and machine learning models to address business challenges across the BFSI sector
  • Work on end-to-end model lifecycle- data exploration, feature engineering, model building, validation, and performance monitoring
  • Leverage AWS AI/ML services, including hands-on work within the AWS Bedrock ecosystem, to build and scale AI solutions
  • Experiment with and adopt Generative AI (GenAI) tools and frameworks to create innovative applications and business solutions
  • Collaborate with cross-functional teams to translate business needs into technical requirements and actionable insights
  • Stay updated with advancements in AI/ML and contribute to the continuous improvement of analytics capabilities
  • Mentor junior team members and foster a culture of data-driven innovation

Qualifications:

  • Educational background in Computer Science, Statistics, or Data Science.

Experience & Skills:

  • 9 to13 years of experience in Analytics, Data Science, or AI, preferably within the BFSI domain
  • Strong programming experience in Python with proficiency in libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, or PyTor
  • Hands-on experience with AWS AI stack (SageMaker, Bedrock, etc
  • Sound understanding of machine learning algorithms, statistical modeling, and data handling techniques
  • Exposure to GenAI tools and frameworks and ability to explore new AI technologi
  • Strong analytical and problem-solving skills with an ability to translate data insights into business actions
  • Excellent communication, collaboration, and stakeholder management skills
  • Demonstrated aptitude for learning and being a team player in a dynamic, fast-paced environment.
  • Prior experience working on AI-driven solutions in the BFSI sector
  • Knowledge of LLM integration or prompt engineering for GenAI applications.
  • Experience with cloud-based model deployment and MLOps practices

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