Senior Vice President - Data Scientist - Risk Analytics & Innovation

Black Turtle; Gurugram District; On-site; INR 6,000,000 - 12,000,000; Full time

Job summary

Black Turtle is seeking a Sr. VP of Data Science for Risk Analytics & Innovation in Gurugram. You will lead a multidisciplinary team to shape risk metrics, build dashboards, and deliver data-driven solutions for risk stakeholders.

You will mentor analysts, deploy advanced analytics and ML, and ensure regulatory outputs. Strong Python/SQL skills, cloud platforms, and excellent communication are essential for success in this role.

Qualifications

• Bachelor's degree in Statistics, Mathematics, Computer Science, or a related field.
• Proven experience leading data science teams and delivering analytics in risk domains.

Responsibilities

• Lead, mentor, and inspire a team of data scientists and analysts to deliver impactful risk analytics.
• Develop and deploy advanced analytics and ML solutions for risk challenges.
• Collaborate with stakeholders to translate requirements into actionable analytics.
• Build and maintain reporting assets to communicate insights to diverse audiences.
• Work with structured/unstructured data to drive decision-making.
• Ensure regulatory outputs are accurate and timely.
• Promote best practices in version control, code quality, and reproducibility.

Skills

Python

SQL

GitHub

Databricks

Power BI

Tableau

Stakeholder Engagement

Mentoring

Communication

Education

Bachelor's degree in Statistics, Mathematics, Computer Science, or related field

Tools

GitHub

Databricks

Power BI

Tableau

Job description

Sr. VP -Data Scientist - Risk Analytics & Innovation

Purpose:

We are seeking a highly capable and curious leader with strong data science experience to lead the Risk Innovation and Analytics team. This role is central to supporting colleagues across the organization-helping to shape, support, and deliver key risk metrics across the design, development, and delivery of data-driven solutions for risk division stakeholders. You will work within a multi-disciplinary team to produce and answer regulatory outputs and enquiries, build interactive dashboards, solve complex problems, uncover insights, and contribute to strategic initiatives across Risk and Enterprise Data & Analytics.

Key Responsibilities:

• Lead, mentor, and inspire a team of data scientists and analysts, aligning efforts to deliver impactful business outcomes.
• Develop and deploy advanced analytics and machine learning solutions to address risk-related business challenges.
• Collaborate with stakeholders to translate business requirements into actionable analytics solutions.
• Build and maintain reporting and visualization assets to communicate insights to technical and non-technical audiences.
• Work with structured and unstructured data sources (e.g., complaints, customer feedback, chat logs) to drive decision‑making.
• Ensure regulatory and compliance outputs are produced accurately and efficiently.
• Champion best practices in version control, code quality, and reproducible analytics.

Capabilities:

• Advanced proficiency in Python (or R) and SQL for data transformation and analytics.
• Confident with version control tools such as GitHub.
• Experience working with cloud-based or enterprise data science platforms (e.g., Databricks, similar environments).
• Ability to understand, develop, and apply advanced analytics and machine learning techniques.
• Skilled with data visualization tools (e.g., Power BI, Tableau).
• Strong stakeholder engagement and communication skills.
• Skilled at translating business content and requirements into actionable analytics solutions.
• Proven ability to lead, inspire, and mentor teams while aligning efforts to deliver impactful business outcomes.
• Comfortable presenting insights and recommendations to both technical and non-technical audiences.
• A growth mindset with a passion for continuous learning and innovation.

Experience:

• Proven experience developing advanced analytical solutions in a business environment.
• Domain expertise in risk (e.g., credit, operational, or regulatory risk) is highly appreciated.

Qualification Requirements:

• Bachelor's degree in Statistics, Mathematics, Computer Science, or a related field; or equivalent industry experience.