Director, Research Science (P1072)

Key Skills

Apache Hadoop, Azure, C Programming, C++, Computer Vision (CV), Continuous Integration & Continuous Delivery - CI/CD, Databricks, Deep Learning, Kubernetes-K8s, Machine learning techniques, MLOps tools, Natural Language Processing (NLP), PowerBI, PySpark, Python Programming, Reinforcement Learning, SPARK Programming, Tableau, TensorFlow

Job Description

We are a community of data scientists that work to improve the experiences of our customers. We leverage large volumes of data to develop powerful sciences and actionable insights using cutting edge machine learning, natural language processing, and mathematical techniques to improve products, processes, and systems that positively impact our customers. We lead our organization in identifying and adopting the tools and technologies that will continue to position our company as the recognized data science leader within our industry.

The Director, Research Scientist – Optimization is a data science leadership role expected to drive forward complex optimization, operations research, and development for the 84.51° / Kroger enterprise. This role sits within the 84.51° Labs Research COE but will drive thought leadership across the enterprise.

The role will employ deep research and optimization expertise to improve, create, and innovate using data and complex analytics to solve current complex business problems while anticipating and charting future research needs. The role has strong research, prototyping, and project collaboration. This research scientist will create new optimization methods through a combination of foundational research and collaboration with ongoing initiatives within 84.51. Also, the role has computational elements, where candidate will have the opportunity to develop, design, prototype, and lead the implementations of new optimization algorithms for large data sets.

Responsibilities

• Specific role presents the opportunity to develop applications for real-time optimization & decision making; price, promotion, and assortment optimization; demand forecasting (in-store & ecommerce); supply chain network; and ecommerce inventory control.
• Mentor and motivate a team of data scientists and researchers to ensure they are given the support and guidance they need to carry out their role successfully; may contain direct management accountabilities of 1-3 research scientists.
• Ensure application viability for real time data driven decision making.
• Develop methods for deterministic, as well as stochastic optimization / optimization under uncertainty algorithms for large scale problems.
• Develop novel optimization methods that utilize recent development in Machine-Learning areas.
• Develop novel numerical techniques to improve computational efficiency.
• Help identify and lead opportunities for data science innovation and research within the team through constant exploration of innovative technologies, methodologies, and approaches.
• Serve as team expert on methodologies, sciences, and solutions relative to optimization space.
• Lead development, planning, and technical evaluation, etc. for key Labs initiatives applied to optimization capabilities.
• Maintain external visibility through conferences, industry events, etc.

Qualification, Skills & Experience

• PhD in computer science, computer engineering, mathematics and statistics, operations research or related subjects. Outstanding and recognized contributions in the retail or customer domain space may in some exceptional cases be an acceptable substitute for the PhD degree when the focus of the specific role is more applied rather than foundational research.
• Research experience and track record of high-quality peer-reviewed scientific publications in the technical domain, and/or other peer-reviewed recognitions of technical contributions including conference presentations.
• 7+ years’ analyzing large-scale network optimization problems.
• 7+ years’ experience with real-time optimization/decision making models.
• 7+ years developing analytical solutions using advanced optimization methods and machine learning algorithms.
• Demonstrated ability to self-direct one’s own research and set the research agenda for more junior research scientists.
• Demonstrated experience mentoring and developing research scientists
• Track record of accomplishment researching Optimization/Machine Learning capabilities; minimum 7 years of experience
• Demonstrated ability to apply research results to problems that arise in retail, manufacturing, and market science.
• Computational sophistication. Experience with Python, including Tensorflow and Spark. For some research scientist roles, experience with such languages as C or C++ and development or prototyping experience is desirable.
• Proven experience deploying real-time learning and real-time decision-making sciences to solve retail business problems, driving significant measurable value
• Strong ability to communicate results, and expertise with visualization of large complex data sets

Skills:

• Programming Skills: Python, Pyspark, AI/ML toolkits (sparkml,pytorch,tensorflow)
• Platform Knowledge: Azure, Hadoop, Databricks
• AI: Computer Vision, NLP, Reinforcement Learning, Deep Learning, Process Automation
• Machine Learning: Supervised & Unsupervised Learning, Optimization at Scale, Forecasting, insight platforms at scale
• Visualization: Tableau, PowerBI
• Systems Knowledge: Unix, bash
• Micro Services: Knowledge of API, Containerization, Kubernetes, AKS
• Software Engineering: Devops, CI/CD tools, MLOPS
• Data Engineering knowledge: building data pipelines, kafka (Pubsub), data modelling, data mesh,
• Automation: Airflow or Azure Data Factory