IT Manager Data Science - Military Veterans

ABC Supply is North America's largest wholesale distributor of exterior and interior building products.

ABC Supply is proud to be an employee-first company. In fact, we have won the Gallup Great Workplace Award every year since its inception in 2007, and Glassdoor has named us one of the best places to work in the country. Be part of a company that recognizes your talents, rewards your efforts, and helps you reach your full potential. At ABC Supply, we have YOUR future covered.

Summary:

As the Manager of Data Science, you will be responsible for leading and managing our data science team, driving data-driven initiatives, and contributing to the overall data strategy of ABC Supply Co. You will collaborate closely with enterprise analytics and business teams to identify business challenges, develop innovative data science solutions, and provide actionable insights. Your role will be instrumental in shaping our data science capabilities and ensuring the successful execution of analytics projects.

Essential Duties and Responsibilities:

• Lead and mentor a team of data scientists, providing guidance, technical expertise, and support to ensure the successful execution of projects. Foster a collaborative and innovative team environment.
• Oversee, in conjunction with Product Owners, end-to-end data science projects, from problem definition and data exploration to model development, validation, and deployment.
• Apply advanced statistical and machine learning techniques to analyze complex datasets, extract meaningful patterns, and develop predictive and prescriptive models.
• Contribute to the development of the company's data strategy by identifying opportunities to leverage data science to enhance business processes, optimize operations, and drive revenue growth.
• Collaborate with key stakeholders from various departments within the company, including the National Support Centers, Field Operations, and Branch Operations to understand their data needs and deliver solutions to meet business objectives.
• Stay updated with the latest advancements in data science, machine learning, and AI technologies. Evaluate and implement new tools, algorithms, and frameworks to enhance the team's capabilities.
• Ensure the team creates and maintains documentation using appropriate tools, including wikis for narrative documentation and version-controlled repositories for technical documentation.
• Operate in agile environment intended to facilitate iterative development and continuous delivery.
• Effectively communicate with colleagues on both technical and non-technical topics, across a variety of communications platforms, including voice and video calls, chat, and email

• 5+ years of experience in data science, with a proven track record of leading successful data science projects and managing teams
• Significant experience extracting data from databases or other sources with SQL
• Significant experience with at least one of Python or R, and common packages used for data wrangling (e.g. pandas, tidyverse), modeling (e.g. scikitlearn, caret/tidymodels), and data visualization (e.g. seaborn, ggplot2)
• Significant experience in at least one "non-wrangling" data science domain, e.g. optimization, clustering/segmentation, supervised learning, time-series forecasting
• Significant experience with descriptive and inferential statistics, e.g. hypothesis testing, confidence intervals, correlations, etc.
• Significant experience with at least one enterprise data visualization tool (Tableau preferred)
• Experience with at least one cloud data platform (Azure and Snowflake preferred)
• This role is likely best suited toward candidates with a master's degree and 7-10 years of related experience.

• Health, dental, and vision coverage - eligible after 60 days, low out of pocket
• 401(k) with generous company match - eligible after 60 days, immediately vested
• Employer paid employee assistance program
• Employer paid short term and long term disability
• Employer paid life insurance
• Flex spending
• Paid vacation
• Paid sick days
• Paid holidays