Dana Bukenova

About Dana Bukenova

I’m a Senior Product Data Science Leader working at the intersection of product strategy, experimentation, and applied machine learning in large-scale B2B SaaS environments.Over the past 8+ years, I’ve helped enterprise products understand how growth actually happens - by designing rigorous measurement systems, building predictive models, and running experiments that inform roadmap decisions, retention strategy, and AI adoption.At Bloomberg, I lead product data science initiatives across highly cross-functional teams, partnering with Product, Engineering, Design, and Commercial leadership. My work focuses on defining and operationalizing KPI architecture (MAU, retention, stickiness, feature breadth), evaluating GenAI features in production, and translating complex behavioral data into decisions that directly impact product direction and revenue outcomes.My core strengths include- Product measurement & KPI architecture that connects user behavior to business value - Experimentation & causal inference (A/B testing, quasi-experiments) to reduce product risk- Predictive modeling & ML for retention, usage forecasting, and expansion signals- Enterprise-scale usage analytics across multi-product, seat-based platforms- AI / LLM feature evaluation & adoption strategy (assistant usage, AI answers, agentic workflows)Before Bloomberg, I built and led analytics functions in telecommunications and enterprise SaaS, including creating consumer and product analytics practices from the ground up.Technical stack:SQL • Python (pandas, scikit-learn) • Databricks / Spark • AWS Redshift & Athena • Amplitude • Mixpanel • Tableau • Event instrumentation • Experimentation platforms • Git/GitLab • Confluence

Experience

1. Senior Product Analytics Manager

   Bloomberg Industry Group

   Jun 2022 — Present · US

   Led product analytics for Bloomberg Law, partnering with PMs and Engineering to instrument Amplitude, standardize event tracking, and build scalable product health KPIs that improved adoption, activation, and feature usage.• Defined and delivered the cross-functional analytics roadmap, aligning priorities across Product, Engineering, Commercial, and AI teams to influence long-term data strategy.• Built ML-driven retention and renewal models for large law firms and corporations, enabling early risk detection, targeted interventions, and more accurate revenue forecasting.• Developed predictive models and executive dashboards identifying high-value accounts and champions, resulting in $325K in incremental annual revenue (BTOP — Winner).• Led experimentation for AI and recommender systems, improving personalized experiences and lifting user engagement.• Presented insights to senior leadership, translating complex data into clear recommendations that shaped product direction and investment decisions.

Education

• Kenzhegali Sagadiyev University of International Business (UIB)

  Bachelor of Science (BS), Finance

• The University of Manchester

  MSc, Marketing

• Association for Institutional Research

  Certificate of Completion, Data Analytics

  2020 — 2020

• The University of Manchester

  Master of Science - MS, Marketing

• Kazakh Ablai Khan University of International Relations and World Languages

  Bachelor's degree, International Relations and Affairs

Skills

• Telecommunications
• Product Development
• Market Analysis
• Marketing Research
• Strategy
• Spss
• Adobe Photoshop
• Consumer Behaviour
• Microsoft Excel
• Fmcg
• Business Development
• Consumer Marketing
• Consumer Behavior
• Marketing
• Online Marketing
• Customer Intelligence
• Microsoft Powerpoint
• Management
• Microsoft Word
• Marketing Strategy
• Market Research
• Marketing Analytics
• New Business Development
• Project Planning
• Competitive Analysis
• Market Planning
• Consumer Insight
• Sql
• Data Analysis