Sr Data Scientist

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Job Location: Dallas, Texas

Are you passionate about solving challenging problems and driving innovation? At Hershey's, we are looking for builders and innovators to create scalable decision-making solutions and apply machine learning and statistical techniques to shape the future of snacking.

As a Sr. Data Scientist, you will be challenged to work across teams and organizations to put theory into practice through experimentation and invention,develop new algorithms for complex problems, implement prototypes, and work with complex datasets. You will directly impact Hershey products known and loved by hundreds of millions of consumers, driving real-world results. Utilizing advanced analytics, you'll forecast trends, understand customer preferences, and optimize business outcomes.

This role is a fully autonomous individual contributor who owns end-to-end delivery of complex scientific problem areas within a defined domain. Operating with minimal guidance, the position translates ambiguous but bounded business objectives into robust, production-ready modeling approaches. The individual is accountable for delivery, scientific quality, methodological rigor, and technical decision-making within their scoped area. Close partnership with engineering, product, and business stakeholders ensures solutions align with approved architectures and business priorities. The primary measure of impact is reliable ownership of complex scientific initiatives, elevated scientific quality, and sustained improvement in team-level execution.

With a focus on innovation and entrepreneurship, Hershey offers an environment that is dynamic, compelling, and rewarding-where data is not just numbers but the key to delivering moments of happiness to consumers worldwide andcreating the future of snacking.

Basic Qualifications:

• Master's degree inOperations Research, Statistics, Optimization, Operations Management, Machine Learning, Applied Mathematics, or other related fields
• Proficiency in at least one modern programming language such as Python, Java, or C++
• Basic proficiency with SQL
• Ability to design and implement solutions using both toolkits and custom-developed code
• Demonstrated ability to present business cases and scientific models with rigorous analyses that support conclusions to influence and drive important decisions
• Strong fundamentals in problem solving, algorithm design and complexity analysis
• Excellent written and verbal communication skills for cross-team coordination
• Proven experience in mentoring and growing teams of scientists
• 4+ years of hands-on experience in the relevant field

Preferred Qualifications:

• PhD degree in Operations Research, Statistics, Optimization, Operations Management, Machine Learning, Applied Mathematics, or other related fields

• Extensive experience with Cloud Platforms such as Azure, AWS, or GCP, including their data processing and machine learning toolkits.
• Proficiency with Optimization Solvers such as Gurobi and Xpress, or experience integrating optimization algorithms into large-scale systems.
• Hands-on expertise with Big Data Analytics tools, including Scikit-learn, Keras, TensorFlow, Pandas, NumPy, and PySpark.
• Demonstrated ability to work within interdisciplinary teams, leveraging cutting-edge machine learning and data science methodologies.
• Experience in designing and deploying scalable and production-grade predictive and prescriptive models.
• Strong knowledge of data visualization techniques and tools to effectively communicate insights.

#LI-Hybrid

The Hershey Company is an Equal Opportunity Employer. The policy of The Hershey Company is to extend opportunities to qualified applicants and employees on an equal basis regardless of an individual's race, color, gender, age, national origin, religion, citizenship status, marital status, sexual orientation, gender identity, transgender status, physical or mental disability, protected veteran status, genetic information, pregnancy, or any other categories protected by applicable federal, state or local laws.

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