Intuit SBSEG Data Science has an exciting opportunity to be part of the fast-growing Mid-market Data Science team that plays a critical role in driving growth in Mid-market with a long-term winning strategy. Disrupt the small business mid-market is one of Intuit’s Big Bets initiatives.
The Mid-market Data Science team is responsible for (1) providing valuable insights that supports the development of E2E strategy, operational plans and product roadmaps; (2) providing data/tools/actionable insights/experimentation for the execution of multiple Mid-market priorities across our function domains (Product, Marketing, Sales, Customer Success, Finance), developing/managing the success KPIs and reporting as the single source of the truth for how the mid-market business is doing; (3) Develop advanced Data Science capabilities such as product recommendation and lead scoring model.
We are looking for a Senior Staff Data Scientist, who is intellectually curious and extremely self-driven, with a proven track record of leading data science support for a critical or high-growth business areas. The ideal candidate will also have a passion for operationalizing data-driven insights into action through influencing the velocity and quality of learnings, while demonstrating a problem-solving and extreme ownership mindset.
Responsibilities
- Influence strategic business decisions and operational decisions by conducting customer segmentation and profiling, product analytics, sales funnel analysis, sales win/loss analysis, voice of customer analysis, etc.
- Develop and manage key success metrics and leading indicators for providing holistic understanding of how the business is performing and whether each initiative/program is delivering the desired outcomes.
- Proactive explore and identify new business opportunities to help business partners to achieve business goals.
- Communicate data and insights effectively to business partners of all levels including senior leadership team.
- Develop ML models and LLM applications to address business problems.
- Collaborate with data scientists and data engineers across different analytics teams to work on cross-functional projects or develop analytics capabilities.
- Coach and develop junior data scientist in the team.
