Data Scientist, R&D

Join the R&D Agentic Pod at Church & Dwight and help build AI-powered capabilities that support R&D teams with predictive and optimization decisioning. This hybrid role in Princeton, NJ focuses on designing, deploying, and scaling analytics products that turn data into action, with measurable commercial impact.

Compensation: The U.S. base salary range for this full-time position is $71,000– $101,100 per year, and the role is also eligible for a bonus. Base pay offered will depend on job-related knowledge and skills, experience, business needs, geography, and internal pay parity.

What you’ll do

• Work with R&D, Quality, Regulatory, and Consumer Insights teams to frame business questions, define decision criteria, and identify analytics opportunities based on business value, feasibility, data readiness, scalability, risk, and strategic alignment.
• Develop predictive, prescriptive, segmentation, recommendation, propensity, forecasting, causal, experimental, and optimization solutions using structured and unstructured data.
• Build and maintain machine learning models in Python using scikit-learn, XGBoost, or comparable frameworks, including validation and ongoing monitoring.
• Define features, assumptions, validation methods, performance metrics, and monitoring plans; evaluate bias, stability, explainability, failure modes, and business relevance.
• Design test-and-learn and measurement frameworks that quantify incremental impact and convert results into recommendations, scenarios, and decision tools.
• Create proofs of concept and minimum viable analytical products, embedding models and measurement logic into dashboards, applications, agents, and other decision-support experiences.
• Partner with AI Engineers, GTA, the Enterprise Data Platform, and data engineering to productionize solutions and enable reliable, reusable, analysis-ready datasets, including addressing data quality, coverage, and availability gaps.
• Document methodologies, assumptions, limitations, data lineage, and intended use while ensuring alignment with data governance, privacy, security, and responsible AI requirements.
• Drive adoption through stakeholder communication, training, reusable best practices, user feedback, and continuous improvement.

Requirements

• Bachelor’s degree in a quantitative discipline (Data Science/Statistics/Mathematics/Computer Science/Engineering/Econometrics/Analytics/Operations Research or related).
• 3+ years of experience in data science, advanced analytics, machine learning, decision science, or a related field.
• Demonstrated experience applying statistics, linear algebra, and machine learning to business problems.
• Hands-on experience building and evaluating Python models using scikit-learn, XGBoost, or comparable frameworks.
• Experience with SQL, large structured datasets, data preparation, feature engineering, model validation, and translating analysis into recommendations for non-technical stakeholders.

Preferred qualifications

• Master’s degree in a related quantitative discipline.
• Experience working with R&D, Quality, or Regulatory datasets and Consumer Packaged Goods (CPG).

Tech stack

• Python
• scikit-learn
• XGBoost
• SQL

Benefits

• Medical, dental, and vision coverage
• Basic life insurance
• Paid vacation and sick time
• Paid Parental Leave
• Paid holidays, floating holidays, and vacation days starting in their first year of employment depending on hire date
• 401k retirement plan with company match and profit-sharing
• Discounted Employee Stock Purchase Plan

Work environment

Hybrid: Based in Princeton, NJ. In-person attendance is required Tuesdays, Wednesdays, and Thursdays, with remote work options on Mondays and Fridays.