Sr Director, Data Science and Analytics
New
J
JobgetherData Science Analytics
United StatesFull-TimeDirector
SalaryCompetitive base salary ranging from $319,600 to $479,400 USD for eligible candidates in CA, CT, DC, MD, MA, NJ, NY, VA, and WA; competitive base salary ranging from $298,700 to $448,100 USD for eligible candidates in other U.S. locations.
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Job Details
- Experience
- 8+ years of experience in data science, applied AI, or machine learning, including 5+ years leading and growing technical teams.
- Required Skills
- PythonSQLMachine LearningData scienceFinancial analysisdbt
Requirements
- 8+ years of experience in data science, applied AI, or machine learning.
- 5+ years leading and growing technical teams.
- Proven experience managing analytics teams and driving data-informed decisions.
- Strong statistical and machine learning foundations.
- Hands-on knowledge of modern AI technologies, including LLMs, agentic systems, orchestration, tool use, retrieval, and AI evaluation methodologies.
- Advanced proficiency in SQL and Python.
- Familiarity with modern cloud data and AI ecosystems, including cloud warehouses, dbt, and LLM or AI deployment pipelines.
- Experience translating ambiguous business challenges into practical, measurable technical initiatives.
- Strong ability to communicate complex technical concepts to non-technical executives.
- Demonstrated ability to lead cross-functional initiatives.
Responsibilities
- Own the data science and applied AI roadmap across operational and finance functions, developing solutions such as agentic systems, forecasting models, lead scoring, and decision-support tools.
- Lead, hire, mentor, and develop a data science and analytics team, establishing high standards for technical rigor, experimentation, evaluation, and production quality.
- Identify high-impact business and operational challenges in partnership with operations, finance, and product leaders.
- Oversee finance analytics supporting accounting, FP&A, pricing, and broader financial decision-making.
- Develop AI and agent-based workflows that move beyond prediction toward automated action.
- Partner with data engineering, machine learning engineering, and platform teams to ensure appropriate infrastructure, data quality, and governance.
- Drive analytics-led decision-making by applying advanced analysis and communicating actionable recommendations to executive stakeholders.
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