Leverage expertise in data science to drive strategic insights and decision-making across operational and support functions, influence business outcomes, improve operational efficiency, and contribute to scalable, data-driven solutions across multiple industries.
Requirements
- Proficiency in data manipulation and modeling using SQL, Python, and/or R.
- Experience building statistical, predictive, and analytical models.
- Ability to communicate complex trends and insights through visualizations (e.g., Tableau) and written reports.
- Strong problem-solving skills with the ability to distill ambiguous requirements into actionable analyses.
- Experience with large datasets and distributed computing platforms (e.g., Spark, Hive) is a plus.
Responsibilities
- Translate data into actionable insights through dashboards, presentations, and reports to support leadership and operational teams.
- Build analytical models to detect patterns, anomalies, and root causes in operational data, enabling proactive decision-making.
- Design and execute A/B tests and other experiments to evaluate AI and analytical solutions.
- Collaborate with technical and non-technical stakeholders to understand data structures, business requirements, and operational priorities.
- Apply SQL, Python, and/or R to manipulate, analyze, and visualize large datasets.
- Build domain and product data acumen to inform customer experience and operational strategies.
- Stay updated on industry and academic research to adopt innovative technologies and methods.
Other
- 8+ years of experience in data science, analytics, or business intelligence roles.
- Proven ability to collaborate cross-functionally and influence business decisions at multiple levels.
- Track record of mentoring and developing junior team members is preferred.
- Remote and flexible working options to support work-life balance.
- Inclusive and collaborative company culture.
