Les Schwab: Data Science and Analytics Lead

Bend, OR, United States

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Company Description

Les Schwab Tire Centers bring you the best selection, quality, and service every time on tires, brakes, wheels, batteries, shocks, and alignment services.

Job Description

The Data Science and Analytics Team Lead provides day-to-day direction to a team of employees and contractors delivering analytic products and solutions to help inform business decisions for stakeholders across the Les Schwab enterprise.  In addition, the Data Science and Analytics Team Lead will define and leverage appropriate data science, analytical and reporting tools, and methodologies, have a strong business acumen and an ability to guide and inspire the organization about the business potential and strategy of Data Science and Artificial Intelligence (AI) solutions. The Data Science and Analytics Team Lead role ensures that data science and analytics deliverables and products are developed and maintained using best practices and collaborates with other operational teams to manage the end-to-end lifecycle of deliverables and products from creation through deployment and maintenance.

 

GENERAL % OF WORK TIME

PRIMARY RESPONSIBILITIES/FUNCTIONS

Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions/primary responsibilities.

60%

Serve as Team Leader and Mentor:

  • Establish processes and procedures for data scientists to frame business problems, deliver models, and conduct end-user validation with stakeholders.

  • Establish processes and procedures for designing statistical experiments to test hypotheses posed by business stakeholders.

  • Establish processes and procedures for Business Intelligence Report and Dashboard design, development, testing and deployment.  

  • Allocate data analysis assignments, resolve issues and engage with leadership on progress and potential risks

  • Improve the organization’s understanding of the value of and methods for data science, statistical experiment design and business intelligence.

  • Collaborate enterprise-wide and beyond to identify data driven opportunities and understand constraints; guide, inspire and strategize on data-driven initiatives to add value to the business

  • Provide ongoing training, assessment, development, coordination and skill building of staff required to support effective and efficient department operation that is in alignment with the functional manager's direction

  • Serve as a role model to others on the team by ensuring best practices are followed and taking a leadership role in projects

Serve as Analytics and Data Science DEVOPS product solution lead:

  • Work with the Data Product Manager to define the initial solution and continuous improvement of proprietary analytic models, prototypes and production products by delivering solutions to meet business value and potential and recommending upgrades, maintenance or decommissioning

  • Create repositories of reusable artifacts, catalogs and documentation to improve team efficiency, knowledge transfer and communication

  • Hold vendors accountable for the quality and usability of delivered analytic models and products 

  • Partner with the Enterprise Data Platforms team in continuous improvement processes to help improve the quality of Enterprise Data Platforms, including Master Data, Datalakes, Data Warehouses and other staged data to support production applications and products.

  • Recommend ongoing improvements to data capture methods, scientific and analysis methods and algorithms, etc. that lead to better outcomes and quality, whether owned by the BI Portfolio or other Portfolios

  • Network within IDS and business partner departments to gain business understanding, and to guide and inspire others about the potential applications of data science

Stay current on data analysis best practices and technologies:

  • Help improve the organization’s understanding of the value of and methods for data science, statistical experiment design and business intelligence.

  • Help improve understanding of related technologies and processes to accomplish outcomes related to delivering insights from data.

  • Recommend and manage the tools needed to perform data science, statistical experiment design and reporting.

  • Support the overall maturity of the Les Schwab Data Science, Business Analytics and Reporting program.

Qualifications

Required Technical Skills/Knowledge: 

  • Advanced technical skills that allow the Team Lead to guide team members and step in and do hands-on data science, statistical analysis, or report development when needed.

  • Demonstrated ability to lead and motivate.

  • Knowledge of machine learning (ML) model building processes, model performance management, ML production infrastructure and best practices for deploying models into the business.

  • Adept at building data pipelines and techniques for exploring, cleansing and visualizing data, as well as predictive and prescriptive analytics approaches.

  • Expertise with database programming languages including SQL, PL/SQL, or others for relational databases, graph databases or NOSQL/Hadoop-oriented databases. 

  • Advanced programming experience in at least two languages such as R, Python/Jupyter, C/C++, Java or Scala.

  • Knowledge and experience in statistical and data mining techniques that include generalized linear model (GLM) / regression, random forest, boosting, trees, text mining, hierarchical clustering, neural networks, graph analysis, data sampling, design of experiments, etc.  Familiarity with typical algorithms used by retail businesses (i.e., Churn, Segmentation) preferred.

  • Ability to recommend and select from several data science approaches to meet target outcomes within business constraints using best-practice data science techniques.

Additional Information

Educational/Experience Requirements: 

  • Bachelor’s or Master’s degree in applied mathematics, statistics, computer science, operations research, or a related quantitative field.  Alternate experience and education in equivalent areas such as economics, engineering or physics is acceptable.  

  • Master’s or Ph.D. degree preferred.

  • Experience in more than one area is strongly preferred. 

  • Certified Analytics Professional credential (available through INFORMS.ORG) required.

  • AND minimum of eight (8) years of relevant experience successfully executing data science, analytics and data visualization projects

  • AND minimum of two (2) years of relevant experience as the accountable leader for a team of data scientists, applied statisticians or BI developers

 

Tags: Business Analytics Business Intelligence C++ Clustering Computer Science Data analysis Data Mining Data pipelines Data visualization DevOps Economics Engineering Hadoop Jupyter Machine Learning Mathematics NoSQL Physics Pipelines Python R RDBMS Research Scala SQL Statistics Testing

Perks/benefits: Career development

Region: North America
Country: United States
Job stats:  1  0  0

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