84.51° Overview:

84.51° is a retail data science, insights and media company. We help the Kroger company, consumer packaged goods companies, agencies, publishers and affiliated partners create more personalized and valuable experiences for shoppers across the path to purchase.

Powered by cutting edge science, we leverage 1st party retail data from nearly 1 of 2 US households and 2BN+ transactions to fuel a more customer-centric journey utilizing 84.51° Insights, 84.51° Loyalty Marketing and our retail media advertising solution, Kroger Precision Marketing.

Join us at 84.51°!

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Senior Data Scientist, MLOps

Summary 

As a Senior Data Scientist Engineer, you are joining a community of analysts, data scientists, and software engineers who work collaboratively to drive business value via our rich first-party data. Data Scientists focus on using scientific methods to develop sciences to solve current business problems. These roles pair backgrounds in mathematics and statistics with strong business acumen and experience working with large datasets and relational databases.

The MLOps team is a cross functional team focused on developing and advancing our end-to-end MLOps process for data science. The team is seeking a Senior Data Scientist to help in the development, support, and education of our data science MLOps process. We are looking for a team member who is driven to understand and excel at using technology and programming for data science MLOps practices. We expect this team member to develop into a Python and be hands on. We expect this team member to be/become a skilled practitioner of our tech stack for data science (e.g., Databricks, Spark, Azure, Docker, Github Actions, etc.). This team member must be a lifelong learner who enjoys seeking out new technologies and methodologies to explore as possible future additions to our solutions.   

 Responsibilities:

  • Providing technical data science support including writing hands on code and package development is support of MLOps work
  • Support adoption of MLOPs through direct hands-on methodology development, support, and trainings
  • Partnering with engineering, architecture and Data Science teams to setup long term machine learning workflows and end to end MLOps framework
  • Assist with internal data science education efforts, through occasional training sessions and the creation of documentation.
  • Serve as early adopter of new technology, helping to build out best practices and providing feedback on the tooling to decision makers.
  • Partner with a wide range of technical personas (i.e., engineering, architecture, data scientists…) to identify and implement best practices around software engineering and analytic procedures.
  • Provide formal and informal guidance to data scientists and engineers within 84.51˚. Be responsive on Teams, Stack Overflow, and GitHub, and partner with stakeholders who need assistance with development practices within their teams. Help teams with technology migration efforts when engaged.
  • Apply statistical and analytical techniques to large datasets to uncover insights that shape better business decisions.
  • Help scope and work on projects from beginning to end to ensure that projects are delivered on time, within budget and to brief specification.
  • Delivering analytical plans in support of client or stakeholder roadmap, ensuring that best practices and innovative ideas are adopted.
  • Support the development of best practice and knowledge management, and champion the capture and sharing of knowledge across the data science community.

 Skills:

  • Strong open-source programming (Python, SQL), cloud platform, and statistical package skills. Knowledge of AI/ML tools and applications to solve business problems.
  • Knowledge of MLOps tools and applications
  • Ability to create computationally efficient solutions, applying techniques from statistics, machine learning, and relevant domain
  • Excellent communication skills, particularly on technical topics.
  • Data visualization skills and ability to present technical solutions to non-technical audience.
  • Strong analytical, creative problem-solving and decision-making skills
  • Natural curiosity that welcomes and embraces change and willingness to try new things and to fail.
  • High level of independence; ability to make time-sensitive decisions rapidly and solve urgent problems without escalation.
  • Strong time and project management skills; the ability to balance multiple, simultaneous work items and prioritize as necessary

Qualifications & Experience:

  • Bachelor's degree in mathematics, statistics, computer science, economics, or similar discipline
  • 2+ years of experience in extracting insights from large databases, translating market research into actionable solutions and presenting findings and recommendations to clients or stakeholders
  • 2+ years of experience using advanced algorithms, programming languages, or technologies in the development of technical analytics solutions or capabilities.
  • 2+ years of experience in tech consulting, retail or related professional services
  • Hands-on experience using Python to develop analytical solutions.
  • Experience querying data from relational databases using SQL.
  • Experience with data wrangling, data cleaning and prep, dimensionality reduction.
  • Experience with Big Data concepts, tools, and architecture
  • Experience working in cloud environments (preferably Azure) to deliver data science solutions or capabilities


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Together, we are stronger and can achieve more

At 84.51°, we believe a diverse and inclusive work environment is essential to the work we do as a data science company. Just as no two Kroger customers are alike, no two 84.51° associates are alike. We understand the importance of fostering an inclusive culture: to encourage our associates to bring their authentic selves to work – embracing who they are and celebrating what they can become.

We continually strive to ensure 84.51° is a place where all people feel like they belong, are respected and valued regardless of who they are, where they are from and what experiences they’ve had. By meeting our 3-year D&I roadmap goals and commitments, we will continue our journey towards becoming a destination for diverse, driven, and authentic minds.

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