Lead Data Scientist (Data & Analytics) (Delhi)

As a Lead Data Scientist at our company, your role will involve establishing and growing the internal analytics capability. Initially, you will work closely with Product and Engineering teams to provide high-quality analytical insights, support product decision-making, and enhance our understanding of platform usage, performance, and outcomes. Your experience with financial or market data will be highly advantageous given the nature of our data products.

Key Responsibilities: - Establish the Analytics Function: - Define a vision, scope, and operating model for internal analytics in collaboration with the VP Data and Analytics. - Identify high-impact analytical opportunities aligned with Product and Engineering priorities. - Establish best practices for analysis, experimentation, metric definition, and insight communication. - Build trust in analytics through rigor, clarity, and transparency of methodology.

- Product & Engineering Partnership: - Partner closely with Product Managers and Engineering Leads to support roadmap decisions with data. - Support the definition and refinement of product metrics, KPIs, and success criteria. - Translate ambiguous product and system questions into structured analytical approaches.

- Data Discovery & Extraction: - Discover, access, and extract data from SaaS platforms, APIs, and operational databases. - Write queries and scripts to programmatically retrieve, combine, and prepare data for analysis. - Identify gaps in instrumentation, tracking, or data availability and propose improvements.

- Insight Generation & Communication: - Conduct exploratory and deep-dive analysis to uncover trends, risks, and opportunities. - Apply appropriate statistical and analytical methods to ensure robust conclusions. - Present insights clearly to technical and non-technical stakeholders, focusing on actionability. - Build dashboards or lightweight reporting where appropriate.

- Grow & Scale the Capability: - Expand analytics support beyond Product & Engineering over time. - Coach and mentor team members, monitoring performance and ensuring alignment with business needs. - Help define future hiring needs and capability gaps. - Contribute to building a scalable, organisation-wide analytics function.

Essential Criteria: - Significant experience in analytics, data science, or product analytics within a SaaS or technology environment. - Experience in team leadership within a growing organization. - Strong SQL skills and experience working with large-scale datasets. - Demonstrated experience discovering, accessing, and programmatically extracting data from SaaS platforms, APIs, and operational databases. - Experience writing scripts (e.g. Python or similar) to retrieve, combine, and transform data for analysis. - Strong statistical reasoning and ability to select appropriate analytical methods. - Experience partnering closely with Product and Engineering teams. - Exceptional communication skills, with an ability to translate ambiguous business questions into structured, data-driven analysis. - Comfortable operating independently and setting direction in an emerging function.

Desirable Criteria: - Experience in financial services, particularly working with trading, securities, market, or regulatory data (highly desirable). - Experience establishing or scaling an internal analytics function. - Familiarity with modern analytics tooling (e.g. dbt, BI tools, experimentation platforms). - Experience shaping event tracking or instrumentation standards. - Exposure to data governance and metric definition frameworks. As a Lead Data Scientist at our company, your role will involve establishing and growing the internal analytics capability. Initially, you will work closely with Product and Engineering teams to provide high-quality analytical insights, support product decision-making, and enhance our understanding of platform usage, performance, and outcomes. Your experience with financial or market data will be highly advantageous given the nature of our data products.

Key Responsibilities: - Establish the Analytics Function: - Define a vision, scope, and operating model for internal analytics in collaboration with the VP Data and Analytics. - Identify high-impact analytical opportunities aligned with Product and Engineering priorities. - Establish best practices for analysis, experimentation, metric definition, and insight communication. - Build trust in analytics through rigor, clarity, and transparency of methodology.

- Product & Engineering Partnership: - Partner closely with Product Managers and Engineering Leads to support roadmap decisions with data. - Support the definition and refinement of product metrics, KPIs, and success criteria. - Translate ambiguous product and system questions into structured analytical approaches.

- Data Discovery & Extraction: - Discover, access, and extract data from SaaS platforms, APIs, and operational databa