Data Science & Engineering Lead
Overview:
We’re looking for a hands-on Data Science & Engineering Lead to lead our data strategy and help scale a lean, high-impact team. This role blends leadership, architecture, and deep technical work - from building predictive models to designing the infrastructure that powers real-time decision-making. You’ll partner closely with cross-functional teams (Product, Business, Finance, Tech) and take full ownership of analytics delivery from raw data to actionable insight.
This is a builder’s role - ideal for someone who wants deep ownership, startup pace, and the chance to grow as we scale.
Responsibilities:
- Define and deliver our data strategy - from core infrastructure to insights delivery
- Build and mentor a team of 2–5 data scientists and engineers
- Design and deploy predictive models, recommendation systems, and performance analytics
- Architect, deploy, and maintain scalable data pipelines and analytics tooling
- Own and scale robust data pipelines and ensure data integrity across business verticals
- Collaborate closely with stakeholders across Product, Business Finance, and Tech teams to integrate data into daily operations and product decisions
- Act as the go-to person for data strategy, experimentation, and insights
Requirements:
- 5–6 years of relevant experience in data science, engineering or analytics,
- At least 1-2 years in a leading or mentoring small teams (leading 2-5 people) within an agile high tech environment
- Strong command of Python or R; strong SQL skills required
- Deep expertise in data analysis, predictive modeling, designing scalable pipelines, and maintaining analytics infrastructure
- Familiarity with modern BI tools (e.g., Looker, Metabase, Power BI, Tableau)
- Experience working cross functionally with business and product teams
- Startup mindset; strong bias for action, autonomy and ownership; able to apply agile principles and own delivery end to end
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