Senior Product Data Scientist

SHRM•Alexandria, VA

21h•Hybrid

About The Position

The Senior Product Data Scientist is a senior individual contributor responsible for leading the exploration and evidence generation that informs the development and validation of new products and solutions. This role owns product discovery from early-stage concept exploration through pre-MVP validation, generating evidence to assess customer needs, demand and solution fit, adoption potential, pricing, and willingness to pay. Working with a high degree of independence, the Senior Product Data Scientist partners closely with Product Managers, business leaders, and cross-functional stakeholders to translate complex business and product questions into rigorous study designs and actionable insights. The role serves as a subject matter expert in product, customer, and pricing analysis and is responsible for maintaining analytical quality, methodological rigor, and appropriate scope throughout the product validation lifecycle. The Senior Product Data Scientist operates in an agile environment that leverages internal capabilities, external partners, and artificial intelligence tools to accelerate insight delivery while maintaining appropriate standards for accuracy, quality, and responsible use.

Requirements

Bachelor’s degree in Data Science, Marketing, Business Administration, Economics, Statistics, Data Analytics, Consumer Psychology, Behavioral Science, Sociology, or a related field, or relevant equivalent experience in lieu of degree.
Six (6) or more years of progressively responsible experience in product discovery, pricing analysis, customer insights, or a related analytical discipline.
Demonstrated experience conducting studies with B2B customers and decision-makers; experience within HR, HR technology, B2B SaaS, or related industries preferred.
Demonstrated experience designing and executing complex qualitative and quantitative studies from initial question through analysis and recommendations.
Experience conducting pricing analysis, concept testing, survey and sampling design, segmentation, and other advanced methodologies.
Experience partnering with and influencing senior leaders and cross-functional stakeholders on complex or high-impact business decisions.
Advanced knowledge of product, customer, pricing methodologies, and best practices.
Advanced knowledge of data science, advanced analytics, data-product development, and statistical modeling methodologies and best practices.
Strong knowledge of analytical methodologies, including predictive modeling, regression, classification, clustering, segmentation, forecasting, causal inference, experimentation, optimization, and machine learning techniques.
Advanced knowledge of data collection, data preparation, measurement, experimental design, data quality, model validation, and analytical standards.
Strong quantitative analytical capabilities, including the ability to integrate and analyze complex datasets, identify patterns and relationships, develop and interpret statistical and predictive models, and translate findings into actionable business and product solutions.
Experience developing analytical models, tools, and data products that enable decision-making, improve organizational performance, and create scalable business value.
Proficiency with statistical programming, querying, and analytical tools such as Python, R, SQL, SPSS, or comparable technologies.
Proficiency with Qualtrics or a comparable survey platform.
Proficiency with at least one statistical analysis tool or programming language, such as SPSS, R, or Python.
Advanced proficiency with Microsoft Excel and the ability to analyze and interpret complex datasets.
Strong critical-thinking and problem-solving skills with the ability to distinguish meaningful findings from unsupported conclusions or assumptions.
Ability to translate complex findings and data into concise, actionable recommendations for senior leaders and other stakeholders.
Strong consultation, facilitation, and stakeholder-management skills, including the ability to navigate competing priorities and build alignment around study objectives.
Ability to exercise sound independent judgment and appropriately challenge assumptions while maintaining productive working relationships.
Strong written and verbal communication skills with the ability to present complex findings clearly to diverse audiences.
Ability to manage multiple complex initiatives, priorities, and deadlines with a high degree of independence.
Ability to effectively leverage artificial intelligence tools and technologies to streamline workflows, enhance productivity, and improve overall work quality while applying appropriate validation, quality-control, and responsible-use practices.

Nice To Haves

Experience managing external vendors or partners preferred.
Experience incorporating artificial intelligence or emerging technologies into workflows preferred.
Experience with Sawtooth or comparable conjoint and MaxDiff software preferred.

Responsibilities

Lead product discovery and validation from early-stage concept exploration through pre-MVP validation, assessing customer needs, demand, solution fit, adoption potential, pricing, and willingness to pay.
Translate complex product and business questions into clear objectives, hypotheses, study designs, and research plans using established product evaluation frameworks.
Design and execute data science and product analytics initiatives that translate behavioral, transactional, customer, and market data into scalable insights, predictive models, and decision-support products.
Apply advanced statistical, machine learning, experimentation, and optimization methodologies—including regression, classification, clustering and segmentation, predictive modeling, causal inference, A/B and multivariate testing, conjoint analysis, MaxDiff, pricing optimization, and other techniques to inform product development, personalization, forecasting, and business decisions.
Analyze and synthesize quantitative and qualitative findings into objective, evidence-based insights and recommendations, identifying key opportunities, risks, limitations, and implications for product and business decisions.
Ensure study design, methodology, data quality, and documentation meet appropriate standards for accuracy, consistency, and methodological rigor.
Serve as a subject matter expert and trusted advisor on product, customer, pricing, and validation methodologies.
Partner with Product Managers, business leaders, and cross-functional stakeholders to define business questions, establish objectives, and align on appropriate approaches and scope.
Exercise independent judgment to balance business priorities and timelines while maintaining analytical quality and provide objective recommendations, including when findings challenge existing assumptions.
Communicate complex methodologies and findings clearly to technical and non-technical audiences, including senior leaders, and provide methodological guidance to colleagues.
Leverage internal capabilities, external partners, AI tools, and emerging technologies to improve the efficiency and scale of product discovery while maintaining appropriate quality, professional judgment, and human oversight.
Manage and validate vendor- and AI-supported work and remain current on emerging analytical methodologies, technologies, and industry best practices.