Les Schwab Tire Centers

Job Description:

POSITION SUMMARY:

The Data Scientist II transforms structured and unstructured data into insights and models for business decision-making, embodying Data Mesh principles by treating data as a product. As a member of a federated team, the Data Scientist II performs individual work assignments, participates in working groups, and contributes to enterprise projects, often independently representing the Data Science and BI Team. This role also involves creating self-service analytical tools and templates and collaborating with other teams in the Portfolio and working cross-functionally. The Data Scientist II has a strong business acumen, and this role involves framing business problems as analytical challenges, utilizing appropriate data science methods. The Data Scientist II has a breadth of expertise in data science methodologies and techniques and can select appropriate tools for data access, cleansing, code development, predictive model building, and applying statistical methods for business-validated solutions. Quickly learning new concepts, this position requires minimal supervision, a high breadth/depth of job-specific knowledge, and an advanced level of service delivery, professionalism, and communication.

This role is within the Information and Digital Services organization at Les Schwab headquarters in Bend, OR.

Applicants must be currently authorized to work in the United States on a full-time basis. This position is not eligible for visa sponsorship.

PRIMARY RESPONSIBILITIES:

30% - Operational Support:

• Lead discovery processes of high complexity with stakeholders to define the business problem, understand IT and business constraints and opportunities and understand the qualitative nature of data required to deliver results.
• Transform the business problem into an analytical problem and identify a wide breadth of data science approaches for achieving the desired business insights and criteria for selecting among approaches.
• Apply various Machine Learning (ML) and advanced analytics techniques to perform classification or prediction tasks.
• Assist the Data Science Team Lead in creating high quality summaries of Data Science projects and results for presentation to steering committees and executive groups.
• Assist the Data Science Team Lead in scoping and prioritizing data science projects.

30% - Data Structure and Solution Development/Design:

• Responsible for building data pipelines from various internal data sources (such as point-of-sale, ERP, financial systems, and websites) and external sources (including weather stations, geo-location systems, and social media sites).
• Apply data cleansing techniques like deduplication, hashing, scaling, normalization, dimensionality reduction, fuzzy matching, imputation, and cross-validation.
• Design experiments to gain insights and test hypotheses using quantitative methods.
• Collaborate with data engineers and IT to evaluate and implement deployment options for developed models.
• Proactively engage in continuous professional improvement (technical and soft skills) and contribute to group retrospectives and process improvements for collective work management.

15% - Data Platform Quality:

• Identify the lifecycle of any developed models and insights and develop maintenance plans for ongoing operational use of insights and recommendations.
• Create reusable artifacts and contribute to data and insight catalogs and documentation.
• Partner with data stewards and data platform developers in continuous improvement processes to help improve data quality.
• Recommend ongoing improvements to data capture methods, analysis methods, mathematical algorithms, etc. that lead to better outcomes and quality.

15% - Stakeholder Relationship:

• Present insights and rationale of recommendations in easy to understand terms and guide business stakeholders to validate insights and recommendations, while maintaining the ability and willingness to present data-driven analysis results that may contradict common belief.
• Help improve enterprise stakeholder understanding of related technologies and processes to accomplish data science outcomes, which includes enabling their capability for self-service analytics through the effective use of tools and templates.
• Guide and inspire others about the potential applications of data science.

10% - Resource Development - Best Practices:

• Responsible for being a lead participant in peer reviews and the presentation of specialist data science topics.
• Advance collective team understanding of relevant technologies and techniques to accomplish data science outcomes, particularly those that improve enterprise stakeholder understanding and capability for self-service analytics.
• Network within IDS and business partner departments to gain business understanding.

MINIMUM REQUIREMENTS:

Educational/Experience Requirements:

• Bachelor’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 degree preferred
• Certified Analytics Professional credential (available through INFORMS.ORG) preferred
• AND minimum of 3-5 years of full-time or equivalent relevant experience executing data science projects, preferably in the domains of customer behavior prediction and operations management.

Required Technical Skills/Knowledge:

• Substantial coding knowledge and experience in at least two programming languages: for example, Python/Jupyter, R, C/C++, Java or Scala.
• Experience with database programming languages including SQL, PL/SQL, or others for relational databases, graph databases or NOSQL/Hadoop-oriented databases.
• 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.
• Technical skills for working across multiple deployment environments including cloud, on-premises and hybrid and skills for acquiring new datasets, parsing datasets, organizing datasets, representing data visually and automating data-driven models.
• Experience with statistical tools and advanced analytics platforms such as: Minitab, HEX, SAS, Knime, Dataiku, Data Robot, Anaconda, Google Collaboratory.

Physical Requirements: Primarily desk position; regularly required to sit, occasionally required to stand and walk. Requires frequent and repetitive use of hands and fingers to operate computer, mouse, keyboard, and office related equipment and the ability to reach with hands and arms. Position requires lifting no more than 10 pounds on a regular basis. Specific vision abilities required by this job include close visual acuity and the ability to adjust focus. Requires the ability to communicate verbally and exchange information over the phone and in person.

Work Environment: Office, non-manual work; the worker is not substantially exposed to adverse environmental conditions.

BENEFITS:

• Annual profit-sharing bonus
• Medical, dental, vision for employees
• Company-funded retirement plan - no cost to employee
• Paid holidays
• Paid time off
• Flex remote arrangements (work 1-2 days/week from home)
• Tuition Assistance
• Employee discount

Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions/primary responsibilities. This job description is not all inclusive and is subject to change. Additional duties and tasks may be assigned, as necessary. Employment remains “AT WILL” at all times.