Senior Data Analytics & BI, Global Converse

• Develop, maintain, and evolve analytics products and capabilities that improve operational and strategic decision-making.
• Develop and evolve decision-ready dashboards, KPI frameworks, and self-service analytics products that enable Supply Chain & Logistics partners to monitor performance, investigate drivers, and take action.
• Access, analyze, and model Converse data using SQL, Python, and related analytical tools to generate actionable business insights.
• Translate complex or ambiguous business questions into structured, scalable analytics solutions that primarily support Supply Chain & Logistics, while also enabling Planning, Merchandising, Finance, and enterprise leadership needs.
• Build forward-looking analyses that identify trends, risks, opportunities, and potential business impacts across demand, inventory availability and productivity, order fulfillment, delivery performance, product, channel, and financial performance.
• Create reusable analytical workflows, models, and data products that improve speed, automation, consistency, and scalability of insight generation.
• Partner with business stakeholders to translate analytical outputs into clear, executive-ready recommendations that support growth, profitability, inventory productivity, and consumer outcomes.
• Improve data quality, accessibility, governance, and usability across the modern data stack, including the development and adoption of consistent KPI definitions and reusable semantic models.
• Contribute hands-on across querying, data transformation, feature engineering, statistical modeling, machine learning, and advanced analytics workflows.
• Advance data literacy and foster a stronger data science community within Converse through partnership, knowledge sharing, and practical application of modern analytical methods.
• Explore and apply emerging AI capabilities where they can responsibly accelerate analysis, improve signal quality, or scale decision support.

• Strong technical foundation in data manipulation, statistical modeling, forecasting, optimization, and large-scale data analysis.
• Significant experience applying advanced analytical methods such as regression analysis, time-series modeling, cohort analysis, machine learning, or optimization techniques.
• Ability to design, evaluate, and explain models that surface patterns, forecast outcomes, quantify risk, and identify business opportunities.
• Proficiency in SQL and Python, with experience building reusable analytical workflows and scalable solutions that move beyond one-off analysis.
• Experience working with imperfect or incomplete data and building structured approaches to improve signal quality, reliability, and interpretability.
• Ability to frame ambiguous business problems into analytically tractable approaches and communicate assumptions, tradeoffs, and implications clearly.
• Strong communication skills, with the ability to translate technical methodologies and results into clear recommendations for non-technical stakeholders.
• Experience partnering cross-functionally and balancing priorities across multiple stakeholder groups in a dynamic business environment.
• Curious, adaptable, and creative problem-solving mindset with strong attention to detail and accountability for delivery.

• 5+ years of experience in advanced analytics, data science, business analytics, BI, or related technical roles; retail, consumer, or planning experience preferred.
• Preferred, but not required - Experience applying analytics within Supply Chain, Logistics, inventory management, order management, fulfillment, or related retail operations.
• Proficient in Python development, including pandas, scikit-learn, statistical modeling, forecasting, and optimization techniques.
• Advanced SQL skills, including complex querying, data transformation, analytical modeling, and exposure to data engineering concepts.
• Familiarity with cloud analytics environments and modern data platforms (including Databricks and Snowflake).
• Practical experience applying AI/ML methods, particularly forecasting, predictive modeling, and optimization; exposure to Generative AI, LLM-based workflows, agentic systems, or Retrieval-Augmented Generation is a plus.
• Experience rapidly prototyping analytical solutions and scaling successful approaches into repeatable products or production-ready outputs.
• Advanced understanding of BI and visualization tools; Sigma preferred, Tableau or comparable platforms acceptable.
• Demonstrated ability to turn structured and unstructured data into actionable insights that influence business decisions.
• Experience owning complex projects from problem framing through delivery, adoption, and continuous improvement.
• Solid understanding of planning concepts such as demand, inventory, seasonality, performance management, and business forecasting a plus.
• Bachelor's degree in Business, Analytics, or related field. Will accept any suitable combination of education, experience and training

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