Business Analyst Lead

Key Responsibilities:

- Own the analytics vision and roadmap aligned with overall business strategy; translate priorities into a clear portfolio with milestones and success metrics.

- Lead and mentor the analytics team to deliver high-quality, accurate, and timely outputs; establish standards for analysis, QA, peer review, and delivery SLAs.

- Identify commercial opportunities—growth levers, cost-efficiency plays, and risk signals—and convert insights into action plans with owners, timelines, and expected impact.

- Collaborate closely with Marketing, Product, Finance, and Operations to design data-driven strategies (pricing, funnel optimization, retention, LTV/CAC, unit economics).

- Define, socialize, and track KPIs that align with organizational goals; enforce consistent definitions and adoption across teams.

- Build and maintain analytical assets, data models, marts, dashboards, and executive views to support rapid, confident decision-making.

- Communicate complex analyses in clear, business-friendly language; craft concise narratives and recommendations for senior leadership.

- Provide strategic advisory through scenario analysis, forecasting, sensitivity testing, and business impact evaluation for planning and investments.

- Continuously evaluate and adopt tools, methodologies, and technologies that enhance analytical and business capabilities.

- Champion data governance, privacy, and security while keeping the team agile and business-focused.

- Act as the conduit between analytics and business strategy to ensure insights translate into implemented actions and measured outcomes.

Required Experience & Qualifications:

- Bachelor’s degree in Data Science, Computer Science, Statistics, Business Analytics, or a related field; advanced degree is a plus.

-  5+ years in analytics/BI/data science, including 2+ years leading an analytics or BI team with proven delivery and stakeholder adoption.

- Proven ability to translate business problems into analytical workstreams and deliver measurable impact (revenue uplift, cost savings, risk reduction).

- Executive-level communication skills: craft clear narratives, influence senior stakeholders, and drive adoption of recommendations.

- Strong SQL (advanced) and working knowledge of Python or R for analytics, experimentation, and forecasting.

- Data visualization expertise with Power BI, Tableau, or Looker; designing scalable, executive-ready dashboards.

- Solid grasp of data modeling and ELT/ETL fundamentals; familiarity with orchestration tools (e.g., Airflow, dbt) and Git-based workflows.

- Experience with modern cloud data platforms (e.g., Big Query, Snowflake, Redshift) and integrations/APIs.

- Understanding of KPI design, experimentation, and scenario/forecast analysis.

- Knowledge of data governance, privacy, and security practices, balancing compliance with speed and business agility.