Data Scientist, R&D (AI)

Location: Hybrid in Princeton, NJ, USA; in-person attendance required on Tuesdays, Wednesdays, and Thursdays, with remote work available on Mondays and Fridays.

Base salary: $71,000–$101,100 per year, plus bonus eligibility.

Company

Church & Dwight develops consumer products and operates a Global R&D Innovation & AI organization focused on improving R&D decision-making and operations.

What you will do

• Partner with R&D, Quality, Regulatory, and Consumer Insights stakeholders to identify, prioritize, and frame high-value analytics opportunities.
• Develop predictive, prescriptive, segmentation, recommendation, propensity, forecasting, causal, experimental, and optimization solutions using structured and unstructured data.
• Build, validate, maintain, and monitor machine learning models in Python using scikit-learn, XGBoost, or comparable frameworks.
• Define features, assumptions, validation methods, performance metrics, monitoring plans, explainability approaches, and responsible AI controls.
• Design measurement frameworks, proofs of concept, and minimum viable analytical products, embedding models into dashboards, applications, agents, and decision-support experiences.
• Work with AI Engineers, GTA, enterprise data platform, and data engineering teams to productionize solutions, improve data quality, document methodologies, and drive adoption through communication, training, feedback, and continuous improvement.

Requirements

• Bachelor’s degree required in Data Science, Statistics, Mathematics, Computer Science, Engineering, Econometrics, Analytics, Operations Research, or a related quantitative discipline.
• 3+ years of experience required 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 with 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.
• Knowledge of probability distributions, hypothesis testing, statistical inference, experimental design, causal measurement, supervised and unsupervised learning, forecasting, and optimization.
• Knowledge of data visualization, analytical storytelling, analytical product thinking, model monitoring, data governance, responsible AI, and reliable decision-support solutions.
• Strong technical, business, and product acumen; ability to solve problems in an action-oriented, data-driven way and influence without authority.

Nice to have

• Master’s degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, Econometrics, Analytics, Operations Research, or a related quantitative discipline.
• Experience with R&D, Quality, or Regulatory datasets and Consumer Packaged Goods.

Culture & Benefits

• Collaborative and supportive environment emphasizing courage, determination, ownership, innovation, and accountability.
• Medical, dental, vision, and basic life insurance for eligible employees and dependents.
• Paid vacation, sick time, parental leave, paid holidays, and floating holidays.
• 401(k) retirement plan with company match and profit-sharing.
• Discounted employee stock purchase plan.