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.**

ABOUT INCLUSIVELY

Inclusively is a digital tech platform that empowers job seekers with disabilities, caregivers, and veterans by using Success Enablers–accommodations and personalized workplace modifications that help all job seekers reach their full potential and excel. This includes all disabilities under the ADA, including mental health conditions (e.g. anxiety, depression, PTSD), chronic illnesses (e.g. diabetes, Long COVID), and neurodivergence (e.g. autism, ADHD).

Create your profile, select Success Enablers, and connect to jobs from our partnered employers who are committed to creating diverse and inclusive teams. When registering, you must acknowledge that this platform is for people with disabilities, caregivers, and veterans. However, Inclusively does not require candidates to disclose their specific disability to join the platform.

The Work:

In this role, you’ll be reporting into the Research Principal Director, AI and Data Science, and will work as a senior individual contributor and team lead across a portfolio of client and internal research engagements. The work is highly varied — spanning model-building, client workshops, and thought leadership — and is always tied to real decisions and real audiences.

Key Responsibilities

• 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?

• You’ll have access to 100+ proprietary business data sources through the company Research’s global data lake — the kind of depth you won’t find anywhere else.
• You’ll get a mandate to build at the frontier: agentic pipelines, synthetic intelligence systems, and AI-native research assets that are genuinely new.
• You’ll collaborate with world-class academic institutions including MIT Sloan and The Wharton School, with the opportunity to publish and present externally.
• You’ll have dedicated time to develop novel methodologies beyond immediate project constraints — because we believe great research needs room to breathe.
• You’ll gain leadership exposure across the company’s global industry and capability networks, working with senior stakeholders across sectors.
• You’ll join a team that values auditability, rigor, and craft in every analytical deliverable — and that holds itself to that standard.

The work location for this role will include a mix of working remotely and working onsite. With all our roles, there is some in-person time for collaboration, learning and building relationships with clients, peers, leaders and communities. As an employer, we will be as flexible as possible to support your specific work/life needs.

Here's 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

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