Data Science and Analytics Team Lead
Amazing opportunity with one of the Nations’ Largest Retailers!
Reporting to the Business Intelligence Portfolio Manager, 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 enterprise.
About the opportunity
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.
This role is within the Information and Digital Services organization at their headquarters in Bend, OR.
Primary responsibilities/functions you are responsible for:
60% of your time will be spent performing the following-
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
20% of your time will be spent performing the following-
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
15% of your time will be spent performing the following-
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 their Data Science, Business Analytics and Reporting program.
5% of your time will be spent performing the following-
Other duties as assigned
Minimum Education & Skills Required:
- 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
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.
General Knowledge and Abilities:
- Innovation Skills: Knowledge of when and how to challenge the status quo and ability to identify data-driven and machine learning opportunities. Ability to discover new data sources and attributes and catalog data. Familiarity with inventive and prototyping processes.
- Analytical Skills: Strong analytical and decision-making skills. Understanding of bias and knowledge of methods for cross-validation.
- Communication: Ability to communicate technical, non-technical, and complex concepts clearly and professionally (both verbally and in writing) while ensuring that the quality and content of the message are relevant to the circumstances and understandable to wide audiences; the ability to draft, proofread, and send written communications effectively; the ability and willingness to carefully listen to others by asking appropriate questions, avoiding interruptions, and the leadership to collaborate internally, cross-functionally, and across management levels in formal and informal settings to understand cross IT and business constraints.
- Flexibility: Willingness to work in an ever-changing environment with the ability to positively adapt to organizational, process, and technology changes
- Initiative: Ability to architect technical solutions without close supervision and to execute work assignments of high complexity and diversity
- Leadership: Ability to train, coach, and motivate staff, delegate and make work assignments; exercise independent judgment in assignment and direction of employees; make well thought-out decisions after evaluating and weighing different information and options; and act as a point person for emergent and day-to day issues
- Organization: Ability to manage work assignments through prioritization, paying attention to detail, and optimal time management; ability to handle interruptions with ease and concentrate on several areas of work at one time
- Service Excellence: Lead by example, exhibiting the willingness to be stakeholder-focused by anticipating and understanding stakeholders' needs; collaborate with them to reach a suitable solution; then consistently meet and deliver on those expectations
- Teamwork: Ability to establish and maintain cooperative working relationships with business users and team members; must work effectively independently, as a member of a team, and as a team leader