AI & Analytics Innovation Senior Product Specialist

Senior Product Specialist role focused on rapid analytics and AI prototyping for client engagements within Deloitte's Strategy & Transactions team. The role involves framing business questions, assessing data, building proof-of-value prototypes (dashboards, predictive models, AI-enabled analytics), and preparing handoff packages for implementation teams. Experience with Python, SQL, Git, and LLMs is required.

What you'd actually do

  1. Frame high-value business questions, define KPIs, and develop hypotheses that drive actionable analysis for deal teams and clients.
  2. Assess data sources, evaluate quality and feasibility, and define minimum viable datasets to support rapid analytics delivery.
  3. Rapidly build proof-of-value prototypes and MVPs-including dashboards, predictive models, segmentation analyses, and AI-enabled analytics-using real client data.
  4. Apply reusable frameworks, templates, and accelerators to compress delivery timelines and reduce project risk.
  5. Establish lightweight data governance, metric definitions, and documentation to ensure solutions are sustainable beyond initial delivery.

Skills

Required

  • Python for analytics and modeling (e.g., Pandas, NumPy, scikit-learn; stats models for inference/forecasting; Plotly/Matplotlib for visualization or similar libraries)
  • Applied modeling: e.g., regression/classification, tree-based models (random forest, GBMs), clustering/segmentation, and time-series forecasting basics
  • Structured Query Language (SQL) for data extraction and transformation (CTEs, window functions, query readability)
  • Git and collaborative workflows (PRs, code review, reproducibility)
  • LLMs and AI-assisted development in day-to-day work: coding with AI assistants, using APIs for data collection, and integrating AI into analytical workflows
  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • Ability to lead projects or workstreams
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
  • Strong interpersonal skills and professional demeanor
  • Ability to meet deadlines
  • Ability to provide clear guidance to others

Nice to have

  • cloud data platforms/warehouses (e.g., Snowflake, BigQuery, Redshift)
  • Spark (e.g., Databricks/EMR)
  • communicating analytical insights through dashboards or visualizations using Tableau, Power BI, or Python visualization libraries
  • producing reliable reporting datasets: basic pipeline thinking, refresh schedules, data quality validation
  • Strong foundation in statistics (confidence intervals, regression interpretation, bias/variance intuition) and evaluation discipline (train/test splits, cross-validation, leakage awareness, appropriate metrics)
  • dbt, Airflow, or equivalents
  • data quality tooling/practices
  • fi

What the JD emphasized

  • rapid analytics
  • AI prototyping
  • proof-of-value solutions
  • AI-powered tools
  • AI-enabled analytics

Other signals

  • rapid prototyping
  • proof-of-value solutions
  • AI-powered tools
  • dashboards
  • predictive models
  • segmentation analyses
  • AI-enabled analytics