What are the responsibilities and job description for the Data Scientist position at The Hershey Company?
Job Location: Dallas, Texas
This position is hybrid located in our Frisco office.
Summary
At Hershey, data isn’t just about numbers—it’s about shaping the future of snacking. Our data scientists use advanced analytics to understand customer preferences, forecast industry trends, and optimize operations. In this role, you’ll work on projects that directly impact the Hershey products people know and love—driving real-world results and creating more moments of goodness. You will apply scientific principles to analyze complex datasets, support business decision-making, and develop scalable algorithms and models.
The ideal candidate is an economist specializing in empirical industrial organization or related fields involving structural or reduced-form causal inference. You are a self-starter who thrives in ambiguity, earns trust in a fast-paced, ever-evolving environment, and balances big-picture thinking with attention to detail. You hold yourself to high standards and consistently deliver results.
Major Responsibilities
This position is hybrid located in our Frisco office.
Summary
At Hershey, data isn’t just about numbers—it’s about shaping the future of snacking. Our data scientists use advanced analytics to understand customer preferences, forecast industry trends, and optimize operations. In this role, you’ll work on projects that directly impact the Hershey products people know and love—driving real-world results and creating more moments of goodness. You will apply scientific principles to analyze complex datasets, support business decision-making, and develop scalable algorithms and models.
The ideal candidate is an economist specializing in empirical industrial organization or related fields involving structural or reduced-form causal inference. You are a self-starter who thrives in ambiguity, earns trust in a fast-paced, ever-evolving environment, and balances big-picture thinking with attention to detail. You hold yourself to high standards and consistently deliver results.
Major Responsibilities
- Apply rigorous economic thinking and econometric methods to deliver data-driven recommendations
- Design and analyze experiments and quasi-experimental studies
- Collaborate with scientists to build econometric models and develop scalable solutions to complex problems
- Partner with cross-functional teams—including executives, product, marketing, and finance—to apply economic theory and data insights to strategic initiatives
- Translate ambiguous business problems into data science questions and analyze complex datasets to inform decisions
- Apply scientific principles and methodologies, adhering to best practices
- Proactively identify opportunities and develop innovative solutions
- Create metrics to quantify the business impact of your work
- Write clear, technically accurate documentation and reports with appropriate mathematical rigor
- Communicate model approaches and outcomes effectively to non-technical stakeholders
- Collaborate across science, data, engineering, product, and business teams
- Influence multiple teams and advise senior leadership
- Evaluate cross-team perspectives and model interactions among teams, processes, and systems
- Leverage deep business understanding and data science expertise to identify high-impact solutions
- Shape technical and business strategy, resolve complex issues, and align diverse viewpoints
- Optimize interconnected systems and improve integration across team solutions
- Enhance others’ work through collaboration and by sharing advanced tools and techniques
- PhD in Economics or a related field
- Experience analyzing both experimental and observational datasets
- Proficiency with statistical software (e.g., R, MATLAB, SAS, Stata, Python with NumPy) or domain-specific tools (e.g., TensorFlow for ML)
- Basic proficiency in SQL
- Strong skills in model development, validation, and implementation; experience with ML model deployment is a plus
- Record of patents or publications in top-tier peer-reviewed journals or conferences
- Deep expertise in empirical industrial organization
- Strong background in econometric modeling of preferences and strategic effects
- Solid foundation in statistical methodologies and their application to business problems
- Effective communication skills with both technical and non-technical audiences
- 3 years of experience applying quantitative research to business optimization using ML, deep learning, or operations research
- Experience developing one or more of the following: A/B testing platforms, forecasting models, inventory optimization, capacity planning, pricing strategies, recommender systems, classification models, causal inference tools, or customer choice models