Data Scientist
https://careers.thehersheycompany.com/us/en/job/110181/Data-Scientist
The Enterprise Data Science team within Hershey Information Systems provides exciting opportunities to innovate using machine-intelligent algorithms in a fast-paced team environment that contribute to game-changing projects and transformational technologies. As a data scientist on the Enterprise Data Science team, you will partner with technology and business partners to build new, data-driven, machine-intelligent capabilities that impact the business. You will work with large volumes of data, innovative technologies, and advanced methods to solve real business problems. You will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience.
Applicants must have a strong background in machine learning, statistical modeling, feature engineering, optimization, exploratory data analysis, data mining and pattern recognition.
Primary Responsibilities:
- Use machine learning, deep learning and advanced statistical techniques to create scalable solutions to business problems
- Collaborate with business partners, solution managers and data engineers to define and quantify business problems, and help them implement appropriate algorithmic solutions
- Demonstrate understanding of regression/classification, time series forecasting, optimization, natural language processing, image classification, data mining and other machine learning concepts
- Wrangle large datasets, identify critical information, develop and test hypotheses and make data-driven recommendations
- Design, develop and evaluate predictive and prescriptive models
- Influence decision making by synthesizing complex analyses into actionable recommendations for business partners
- Identify business processes that can be optimized through automation
- Communicate technical results to non-technical audiences
Requirements:
- Master’s degree or higher in Statistics, Mathematics, Data Science, Computer Science, Engineering, or a related discipline with a strong focus on use of predictive analytics and optimization to influence real life decisions
- 3+ years of professional experience applying quantitative research to optimizing business decisions using machine learning/deep learning, and/or optimization techniques like operations research; Ph.D. candidates are accepted in lieu of 3+ years of professional experiences
- 3+ years of experience in Python, Scala or R
- 2+ years of experience with major machine learning/deep learning frameworks such as Scikit-learn, TensorFlow and Keras
- Knowledge in modern big data analytics architectures (Hadoop, SQL, HIVE, Spark/SparkR, etc.)
- Experience in building scalable analytical solutions in cloud (e.g., Azure, AWS, or GCP)
- Demonstrated leadership and self-direction, and willingness to both teach others and learn new techniques
- Ability to communicate complex ideas in a clear, precise, and actionable manner
Preferred:
- Prior experience in the Consumer Packaged Goods (CPG) or retail industry
- Prior research and/or professional experience applying data science for supply chain optimization (e.g., demand/supply forecast, network/logistics optimization, inventory optimization)
- Working knowledge in optimization algorithms: simulation, and operations research (linear programming, integer programming, mixed integer programming)
- Working knowledge with one of the solvers: Cplex, Gurobi, or Goolge OR-tools