Senior Data Scientist at Home

Job Title:            Senior Data Scientist
Job Location:     Hershey, PA
***May consider fully remote candidates***
***This position will be posted internally until the close of business on July 1st, 2022***
Summary:
The Enterprise Data Science organization drives value for Hershey by creating disruptive predictive and prescriptive solutions to the Enterprise for analytics and decision-making.
The Sr. Data Scientist will be working with Hershey business partners, technical engineers, data architects, and project managers to ensure data science standards adhere to company best practice and help to deliver rapid impactful benefits.
The Sr. Data Scientist will act as a trusted advisor for Hershey 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'll design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and the customer experience. You will work with a diverse team of business analysts, technical engineers, data architects, and project managers to deliver outcomes aligned with our business partner’s strategy. In addition, you will work directly with the Director of Data Science to ensure consistency and compliance of deliverables to frameworks and governance processes.
Applicants should have a strong background in machine learning, statistical modeling, feature discovery/selection, optimization, exploratory data analysis, data mining and pattern recognition.
Responsibilities:
Data Science Solution Delivery:
Contribute to the agile delivery of business partner strategic roadmaps using best practice data science methods, frameworks, and governance processes
Data Science Domain:
Collaborate with IT and business partners to define, manage and deliver innovative data science solutions to drive growth and adoption of capabilities at Hershey
Data Science Advocacy:
Evangelize future data science solutions identified by Enterprise Data leadership, including innovations such as: machine learning, statistical modeling, feature discovery/selection, optimization, exploratory data analysis, data mining and pattern recognition
Lead and coordinate key cross-functional data science efforts to accelerate value creation for agile execution team outcome delivery through machine learning
As part of a team, use machine learning (ML), deep learning (DL) and other analytical techniques to create scalable solutions for business problems
Interact with business partners, technologists and engineers define and understand business problems, help, and aid them to implement ML/DL algorithms when appropriate
Design, develop and evaluate highly innovative models for predictive learning, content ranking, and anomaly detection
Analyze and extract relevant information from historical data to help automate and optimize key processes
Work closely with technology, business, and engineering teams to drive model implementations and adoption of new algorithms
Using best practice guidance from the Enterprise Data team, oversee the health and evolution of agile execution team data science technologies
Strategic thinker with holistic vison, specific focus on automation of existing processes to drive key business performance
Able to articulate the holistic benefits of data science from a business perspective, while maintaining the relationship with business analysts, data architects, technical engineers, and project managers
Routinely meets with entire execution team (business analysts, data scientists, technical engineers, data architects, and project managers), business stakeholders and the Director for Data Science.  Occasionally meets with senior leaders Enterprise Data and with key business partners.
Minimum knowledge, skills and abilities required to successfully perform major duties/responsibilities:
Working knowledge of agile frameworks
Ability to manage multiple priorities, meet deadlines and produce quality results under pressure
Demonstrated leadership and managerial skills
Strong problem solving and analytical skills
Strong team player, change agent, and advocate
Excellent customer service skills
High energy self-starter
Excellent verbal and written communication skills
Minimum Education:
Masters in a STEM degree required, Ph.D. preferred
Minimum Experience Requirements: 
3+ years of professional experience with applying quantitative research in optimizing human decisions using technologies like machine learning and/or deep learning
2+ years – using major machine learning/deep learning frameworks (e.g., Scikit-learn, PyTorch, TensorFlow and Keras) and algorithms (e.g., CNN, GAN, LSTM, RNN, XGBOOST) 
2+ years of data engineering experience with modern big data analytics architectures (Hadoop, SQL, HIVE, Spark, etc.) on major cloud platforms (e.g., AWS, Azure, Google Cloud)
2+ years programming skill in Python, R, Scala or Java
Working knowledge with modern cloud-based data storage and compute environments (e.g., Snowflake, Databricks in Azure, AI-platform in GCP, etc.)
Experience deploying ML models into discovery/production environment to drive insights using MLOps a plus
Experience working in a agile delivery model a plus
Demonstrated leadership and self-direction. Willingness to both teach others and learn new techniques
Ability to communicate complex ideas in a clear, precise, and actionable manner
Excellent communication and presentation skills, with the ability to articulate new ideas and concepts to technical and non-technical partners
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