Company Background:
Genuine Parts Company ("GPC" or the "Company"), founded in 1928 and based in Atlanta, Georgia, is a leading specialty distributor engaged in the distribution of automotive and industrial replacement parts and value-added services. The Company operates a global portfolio of businesses with more than 10,000 locations across the world. GPC has approximately 50,000 global employees. The Company has operations in the United States, Canada, Mexico, Australia, New Zealand, Indonesia, Singapore, France, the U.K., Germany, Poland, the Netherlands, Belgium, Spain and China.
Position Purpose :
Seeking world-class talent to join the world's leading distributor of automotive and industrial replacement parts and value-added services operating 5,500 locations and servicing more than 20,000 locations in the U.S and Canada. Specifically, this role will function as the Staff Data Scientist of a newly formed team of AI/ML Engineers to build the next models and analytics. Working with a highly talented team, you'll play a key role to build and run one of the world's largest automotive and industrial replacement parts operations.
This is an engineering leadership role with responsibility of leading data science initiatives that drive business profitability, increased efficiencies, and improved customer experience.
This individual must be a technologist & data Scientist at heart and be comfortable in enabling new technology and being hands on with the execution of the strategy. Must exhibit a deep understanding of modern technology stack and agile delivery models, demonstrated focus on customer experience, and must have a proven track record of modernizing technologies.
Close collaboration and alignment with business teams, application development teams and security will be required. As such, exceptional abilities in building and maintaining strong working relationships and organizational savvy will be required. High level communication and presentation skills are required. Ability to attract, retain, and develop engineering talent will be critical.
Responsibilities:

• As a Staff Data Scientist, you'll work on the GPC's Data Science team collaborating with data scientists, AI/ML engineers and product managers to build and augment our AI-driven digital Catalog, Discovery (Search & Recommendations) products. Through your understanding of deep learning, machine learning, linear algebra, probability theory, statistics, and optimization you'll leverage Python, Scala to perform data exploration and analysis, implement algorithmic solutions given specifications, push solutions to our production environment as well as analyze performance and trade-offs to determine the best solution.
• Reviews business context for solutions to company challenges as well as defining the vision and requirements for the solution, recommending potential options, selecting the most optimal option, and the development of a roadmap for the selected solution.
• Understand and follow Agile principles, best-practice software design, participate in code reviews, create a maintainable and well-tested codebase with relevant documentation.
• Initiate both group and one-on-one meetings with senior management in order to gain a clear understanding of business drivers and functional requirements
• Directs the identification and recommendation of appropriate solutions, upgrades, replacements, or decommissioning options incorporating business and technology productivity, usability, and total cost of ownership.
• Communicates the architecture to the stakeholders and collaborates and coordinates with existing domain architects in the formalization and adoption of IT standards and procedures
• Provides oversight on delivery to ensure industry best practices, standards, automation, quality, timeliness, operational readiness, continuous improvement and cost-effective solutions.
• Provide technical leadership and guidance to lead engineers and the technical team within a domain
• Other duties as assigned.

Location:

• GPC has two work locations to choose from, Duluth or Atlanta office.
• We offer a Flexible Work Policy that permits eligible employees to work a hybrid remote schedule.

Desired Qualifications & Experiences:

• MS/PhD in Mathematics, Statistics, Operations Research, Industrial Engineering, Physics, Computer Science, or other related fields
• 8 (or more) years' experience in software engineering, Data Science & technology
• Experience designing and developing deep learning, machine learning, optimization, and statistical models.
• Strong hands-on programming skills in Python. Knowledge of SQL, Spark/equivalent.
• Expertise running queries against data (preferably with Google BigQuery or SQL)
• Expertise in Prescriptive Modeling like optimization, computer vision, recommendation, Search or NLP
• Demonstrated mastery in predictive modeling, data mining and data analysis.
• Demonstrated mastery utilizing statistical techniques to identify key insights that help solve business problems.
• Strong analytical thinking and data visualization skills. Ability to creatively solve business problems, innovating new approaches where required and a passion for solving interesting and relevant real-world problems using Data science approach.
• Ability to clean, transform, manipulate, and analyze large datasets for insights leading to business process improvements or solution development. Background in handling supply chain data will be preferable but not mandatory.
• Experience in designing and running A/B Tests and analyze the Key Metrics
• Experience with cloud computing on at-least one of major providers (Google Cloud Platform, AWS or Azure).

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GPC conducts its business without regard to sex, race, creed, color, religion, marital status, national origin, citizenship status, age, pregnancy, sexual orientation, gender identity or expression, genetic information, disability, military status, status as a veteran, or any other protected characteristic. GPC's policy is to recruit, hire, train, promote, assign, transfer and terminate employees based on their own ability, achievement, experience and conduct and other legitimate business reasons.