The Senior Data Scientist is responsible for modeling complex enterprise problems, discovering insights and identifying opportunities through the use of machine learning, statistical, algorithmic, data mining, and visualization techniques. The Senior Data Scientist will work closely with business and the Data Science team members to design, develop, and implement solutions for the entire organization. primary focus on inventory optimization and assortment optimization. The ideal candidate will bring expertise in supply chain analytics, experience working with cloud platforms such as Google Cloud Platform (GCP), and proficiency with Vertex AI. The role will involve working closely with cross-functional teams to build and deploy machine learning models that improve inventory management and assortment strategies. A strong background in MLOps pipeline development is highly desired to ensure efficient model deployment and maintenance.

ESSENTIAL JOB FUNCTIONS

Design solutions to complex business problems and oversee them through implementation.

Provide mentorship to Data Scientists and Engineers on the team.

Maintain up-to-date knowledge of a variety of machine learning techniques (clustering, decision tree learning, deep learning, etc.) and their real-world advantages/drawbacks.

Maintain up-to-date knowledge of advanced statistical techniques and concepts (regression, properties of distributions, time series analysis, statistical tests and proper usage, etc.) and experience with applications.     

- Develop, test, and implement predictive models to optimize inventory management and product assortment across multiple store locations.

- Leverage machine learning techniques and statistical analysis to identify patterns, trends, and insights from large datasets.

- Build and deploy machine learning models using GCP and Vertex AI to improve inventory accuracy, reduce stock-outs, and enhance assortment decisions.

- Collaborate with cross-functional teams, including operations, supply chain, and IT, to define data requirements and ensure data availability for analysis and modeling.

- Work on end-to-end MLOps pipelines, including model versioning, deployment, monitoring, and retraining to maintain model accuracy and relevance.

- Use data visualization tools and techniques to communicate insights and model performance to stakeholders effectively.

- Identify and implement opportunities to enhance existing processes using data-driven solutions.

- Conduct exploratory data analysis to understand key drivers and challenges in inventory and assortment optimization.

- Assist in developing business cases for new optimization projects and opportunities for machine learning applications in the supply chain domain.

- Stay up to date with the latest developments in machine learning, GCP, and inventory optimization, applying new techniques as necessary to enhance results.

- Mentor junior data scientists and collaborate with other team members to share knowledge and best practices.

SKILLS/EDUCATION/KNOWLEDGE/EXPERIENCE/ABILITIES

Bachelor’s or Master’s degree in Data Science, Computer Science, Supply Chain Management, Operations Research, or a related field.

Hands-on experience with Google Cloud Platform (GCP) and Vertex AI for building, training, and deploying machine learning models.

5+ Years in a Data Science/Machine Learning role or equivalent experience.

Strong communication skills.

Strong skills in Python; including Pandas, Numpy, SciKit-Learn, and experience with notebooks such as Jupyter.

Strong programming skills in Python, R, or similar languages.

Extensive experience with machine learning and statistical modeling. 

Mastery of SQL along with knowledge of database design and optimization. 

Demonstrable ability to develop and implement mathematical solutions to data problems. 

Strong knowledge of project management techniques.

Experience mentoring and performing code reviews.

Knowledge of business processes and their technological implications.                                                                             

-Knowledge of machine learning algorithms and optimization techniques, particularly in inventory and assortment contexts.

Experience with MLOps tools and processes for continuous model delivery and                                                             

Graduate degree in Computer Science, Statistics, Applied Math or related field.

Extensive software engineering experience.

Experience with a high-level programming language such as C. 

Linux/macOS command line experience that includes shell scripting.

Strong knowledge of data visualization best practices.

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O’Reilly Auto Parts has a proven track record of growth and stability. O’Reilly is full of successful career stories and believes in a strong promote-from-within philosophy, encouraging you to grow your career along with the organization. 

Total Compensation Package:

Competitive Wages & Paid Time Off

Stock Purchase Plan & 401k with Employer Contributions Starting Day One

Medical, Dental, & Vision Insurance with Optional Flexible Spending Account (FSA)

Team Member Health/Wellbeing Programs

Tuition Educational Assistance Programs

Opportunities for Career Growth

O’Reilly Auto Parts is an equal opportunity employer.  Hiring decisions are administered without regard to race, color, creed, religion, sex, pregnancy, sexual orientation, gender identity, age, national origin, ancestry, citizenship status, disability, veteran status, genetic information, or any other basis protected by applicable federal, state or local law.

Reasonable Accommodations: Qualified individuals with known disabilities may be entitled to reasonable accommodation under the Americans with Disabilities Act and certain state or local laws.