Data Science Research Manager

About the role

Inclusively is partnering with a global professional services company to hire a Data Science Research Manager. **Please note: this role is NOT an internal position with Inclusively but with the partner company.

The Work:

• Translate complex business problems into well-scoped, researchable analytical questions with clearly defined outputs and success metrics
• Collaborate with research leads, economists, and client-facing teams to embed AI-native tools into project delivery
• Design, build, and deliver ML and GenAI-powered analytical methodologies to support client engagements across multiple industries
• Develop and iterate synthetic persona generation pipelines, including large-scale digital executive personas and behavioral simulation models
• Implement agentic AI workflows using frameworks such as Google ADK, A2A, and MCP protocols on GCP
• Design and maintain real-time intelligence dashboards and AI-as-a-service analytical assets
• Coach and mentor junior data scientists, fostering a culture of technical rigor and business relevance

What's In It For You?

• Access to 100+ proprietary business data sources through the company Research’s global data lake
• Mandate to build at the frontier: agentic pipelines, synthetic intelligence systems, and AI-native research assets that are genuinely new
• Collaboration with world-class academic institutions including MIT Sloan and The Wharton School, with the opportunity to publish and present externally
• Dedicated time to develop novel methodologies beyond immediate project constraints
• Leadership exposure across the company’s global industry and capability networks, working with senior stakeholders across sectors
• A team that values auditability, rigor, and craft in every analytical deliverable — and that holds itself to that standard

What You Need:

• Minimum of 5 years delivering analytical outputs in client-facing or commercial settings, with demonstrated ability to translate technical findings for executive audiences
• Minimum of 5 years applying machine learning methods, including simulations, supervised/unsupervised models, NLP, and time series
• Minimum of 2 years of experience with generative AI — including LLM prompting strategies, retrieval-augmented generation (RAG), and multi-modal models
• Minimum of 2 years of hands-on experience designing and building agentic AI architectures, including tool-use patterns, planning loops, and multi-agent orchestration
• Bachelor’s degree in Data Analytics, Data Science, Strategy, Economics, or a related field with minimum 5 years of work experience
• Master’s degree with minimum 5 years of work experience. PhD is a plus
• Technical Skills:
  • Python (advanced): modeling, data wrangling, pipeline development, and API integration
  • Machine learning: supervised and unsupervised methods, ensemble models, time series, NLP, and text analytics
  • Generative AI: LLM prompting, fine-tuning, retrieval-augmented generation (RAG), and multi-modal models
  • Agentic AI: experience building agent architectures including tool use, planning loops, and multi-agent orchestration
  • Synthetic data generation: methods such as SDV, Gaussian Copula Synthesizer, IPF calibration, or equivalent
  • Google Cloud Platform (GCP) — critical requirement: Cloud Run, BigQuery, Vertex AI, Secret Manager, and GCP deployment architecture
• Soft Skills & Mindset:
  • Strong business acumen: ability to contextualize analytical findings within industry dynamics and C-suite decision-making
  • Excellent communication skills — written, verbal, and visual — for presenting to executive and non-technical audiences
  • Strategic problem-solving mindset: comfortable moving from ambiguous business context to a structured analytical approach
  • Strong project and stakeholder management capabilities in fast-paced, global environments
  • Enthusiasm for cross-functional, multicultural teamwork with a bias toward building durable, reusable infrastructure
• Bonus Points if You Have:
  • Experience designing and facilitating client workshops, co-creation sessions, or executive briefings in a consulting or advisory context
  • Published thought leadership — white papers, industry reports, or HBR-style research — with demonstrated ability to synthesize complex AI topics for non-technical audiences
  • Deep vertical expertise in at least one industry (e.g., financial services, consumer goods, healthcare, energy) with a track record of designing industry-specific AI solutions
  • Experience with synthetic data generation methods (SDV, Gaussian Copula Synthesizer, IPF calibration, or equivalent) in research or commercial settings
  • Background in academic or institutional research collaborations, such as with business schools or think tanks

Pay

Annual Salary Range - $87,400 to $266,300