Job Location: Dallas, Texas

This will be a hybrid role

 This role will not provide relocation support.

 

Summary:

At Hershey, data isn’t just about numbers—it’s about creating the future of snacking. Our data scientists use advanced analytics to understand customer preferences, forecast trends that shape the industry and optimize our business. You’ll have the opportunity to work on projects that directly impact the Hershey products that people know and love – driving real-world results and more moments of goodness. In this role, this individual will apply scientific principles to analyze complex datasets to make business decision while developing scalable algorithms and models. 

 

Major Responsibilities:

 

Translates ambiguous business problems into data science problems. Analyzes complex datasets to inform or make decisions to address those business problems.​ Applies scientific principles and concepts to support significant invention. Uses a range of scientific methodologies and follows best practices for those methodologies.​ Proactively identifies opportunities and solutions to problems. Solutions may require novel techniques or approaches.​ Creates metrics and measurements to quantify the business impact of the work.​ Writes accurate and clear technical documentation and reports, including appropriate mathematical rigor as needed.​ Communicates the approach and outcomes of models clearly and effectively with non-technical stakeholders to build trust.​ Collaborates with stakeholders across a broad set of functions (science, data, engineering, product, business).

 

Scope of Work:

Influences multiple teams to build consensus and advise Sr leadership.​ Evaluate cross-team perspectives and understand how interactions among teams, processes and systems need to be modelled in solutions. ​ Utilize deep understanding of business challenges and the applicability of relevant data science disciplines and interactions amongst systems to identify the most advantageous solutions that deliver significant benefit to the business​ Contributions influence technical and business strategy. Harmonize discordant views and lead the resolution of contentious issues.​ Optimize connected systems using their dynamics. Improve consistency and integration between team’s solutions and the work done by related teams. ​ Improve work done by others either via collaboration or by increasing their scientific knowledge using specialized tools or advanced techniques

 

Qualifications:

Data analytics skills and experience analyzing both experimental and observational data sets​ Deep expertise in one or more of: machine learning, natural language processing, computer vision, operations research, applied mathematics, statistics, econometrics, causal analysis, or similar science discipline.​ Experience developing one or more of: A/B testing capabilities, forecasting models, inventory optimization, capacity planning, pricing, recommender systems, classification models, causal impact, customer choice models, or similar science products.​ Proficiency with math/stats software (e.g. R, Matlab, SAS, Stata, Python numpy) or other domain specific software (e.g. Python/TensorFlow for ML). Basic proficiency with SQL.​ Strong skills in model development, model validation, and model implementation. For ML-related roles, additional expertise in model deployment and ongoing production support.​ Experience in patents or publications at top-tier peer-reviewed conferences or journals.

 

Experience & Education Requirements:

Masters/PhD in a quantitative field (CS, CE, ML, OR, Econ, or related). PhD preferred, with a minimum of 5 years of experience in data science or a related field

 

 

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