Description:
In this role, you'll turn data into decisions by identifying high-value business problems, framing them analytically, and delivering models and insights that improve customer outcomes and product performance. You'll work across exploratory analysis, statistical modeling, experimentation, forecasting, segmentation, anomaly detection, causal analysis, and machine learning, while partnering closely with product, engineering, sales, operations, or finance stakeholders. Your work will not stop at model accuracy: you'll define success metrics, quantify impact, translate findings into business actions, and help teams prioritize based on value, risk, and feasibility. You’ll also contribute to AI-driven analytics using NLP, embeddings, and LLM-assisted workflows for summarization, classification, knowledge extraction, and decision support. The role requires someone who can connect business context with rigorous analysis, explain trade-offs clearly, and influence roadmap decisions with evidence.
What You Bring
- Strong command of Python and SQL for data extraction, statistical analysis, feature engineering, model development, and analytical automation
- You have a deep understanding of statistics and probability, including hypothesis testing, experiment design, A/B testing, regression, causal thinking, and interpreting uncertainty
- You have hands-on experience with a range of machine learning techniques, such as classification, forecasting, clustering, recommendation systems, anomaly detection, and propensity modeling
- You are skilled at framing business problems into measurable analytical questions, defining success metrics, and connecting model outputs to commercial or operational decisions
- You excel at building clear data narratives through dashboards, visualizations, presentations, and concise executive communication
- You demonstrate practical expertise in feature selection, model validation, error analysis, bias identification, and balancing trade-offs between accuracy and usability
- You have exposure to modern AI approaches, including NLP, generative AI, and LLM-assisted analytics (e.g., semantic search, text classification, summarization, prompt-based analysis)
- You are experienced with modern analytics and data platforms, such as notebooks, BI tools, cloud data warehouses, Spark, and large-scale data processing environments
- You have a strong understanding of data quality, lineage, governance, and the discipline required to produce trustworthy and reusable analyses
About You
- 6+ years of data science experience
- You are curious and bring a structured approach to problem-solving, with the ability to break down complex challenges into clear, actionable steps
- You are a strong collaborator who enjoys working cross-functionally and influencing decisions through data
- You are motivated by driving real-world impact, ensuring your analyses and models lead to measurable business outcomes
- You continuously seek to learn and stay current with evolving data science and AI trends