Lead Data Scientist

2 months ago

Bangalore, India Piramal Capital & Housing Finance Limited Full time

About Role:

We are seeking a dynamic Lead Data Scientist to spearhead our BIU team in Bangalore. In this leadership role, you will oversee a team of 3-4 data scientists focusing on Portfolio Retention Analytics and Business Analytics to drive growth. Your expertise in data analysis, machine learning, and strategic thinking will be crucial in guiding your team to deliver actionable insights and support data-driven decision-making within our retail lending business.

Qualifications:

  • Master's degree in Economics, Statistics, Computer Sciences, Mathematics, Operational Research, CA, or Engineering from a reputed college.
  • This role requires 5+ years of experience in analytics, preferably financial services, retail business and at least 1 year in a team lead or managerial position.
  • Proven track record of leading and mentoring data scientists.
  • Strong proficiency in Python, model development, validation, machine learning, NLP, and marketing analytics.
  • Hands-on experience with analytics tools like R, SQL, Power BI, and MS Excel.
  • Deep knowledge of predictive analytics techniques (machine learning algorithms, logistic & linear regression, decision trees, clustering).
  • Expertise in exploratory data analysis (data preparation, exploration, and visualization).
  • Excellent communication and presentation skills.

Key Roles & Responsibilities:

Leadership & Mentorship:

  • Lead, inspire, and mentor a team of 3-4 data scientists.
  • Foster a collaborative and high-performing team environment.
  • Provide guidance and support for their professional development.
  • Strategic Planning & Execution:
  • Define the team's vision and strategy in alignment with business objectives.
  • Set clear goals, priorities, and performance expectations.
  • Oversee project planning, execution, and delivery.

Data Analysis & Modelling:

  • Guide the team in conducting in-depth data analysis and developing sophisticated models.
  • Ensure the accuracy, validity, and robustness of analytical solutions.
  • Stay abreast of the latest advancements in data science and machine learning.

Business Impact:

  • Translate complex data insights into actionable business recommendations.
  • Partner with cross-functional teams to drive data-driven decision-making.
  • Measure and communicate the impact of the team's work.

Stakeholder Management:

  • Build and maintain strong relationships with key stakeholders across the organization.
  • Effectively communicate project progress, findings, and recommendations.
  • Collaborate with senior management to shape the data science roadmap.

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