Senior Data Scientist - Shop Management System

Company Background

Established in 1928, Genuine Parts Company is a leading global service provider of automotive and industrial replacement parts and value-added solutions. Our Automotive Parts Group operates across the U.S., Canada, Mexico, Australasia, France, the U.K., Ireland, Germany, Poland, the Netherlands, Belgium, Spain and Portugal, while our Industrial Parts Group serves customers in the U.S., Canada, Mexico and Australasia. We keep the world moving with a vast network of over 10,700 locations spanning 17 countries supported by more than 63,000 teammates. Learn more at genpt.com.

Position Purpose

We are seeking an experienced Senior Data Scientist to join our newly formed team. The ideal candidate will have a strong background in machine learning, artificial intelligence, and cloud technologies. In this role, you will work closely with cross-functional teams to develop integrated solutions. This role is not a proof-of-concept only role but developing production applications for use by our customers.

You will work in an agile team that is located in Krakow, PL. Our environment is fast-paced with a focus on experimentation and learning. There is significant potential for growth, and you will play a key role in shaping the direction of our products. If you are passionate about leveraging data to drive business decisions, develop solutions, and have a strong background in machine learning, artificial intelligence, and cloud technologies, we encourage you to apply for this exciting opportunity.

Responsibilities

Key Responsibilities and Accountabilities

• Develop machine learning models that can be connected to applications

• Build and deploy artificial intelligence applications that enable automation and optimization across within the shop management business domain

• Develop generative AI applications leveraging LLMs and SLMs

• Collaborate with cross-functional teams to identify opportunities for data-driven decision making and drive the adoption of machine learning and artificial intelligence across the organization.

• Utilize Cloud technologies such as Google Cloud Platform for AI-powered business applications

• Work with large and complex datasets to extract meaningful insights that drive business value.

• Communicate findings and recommendations to stakeholders at all levels of the organization.

• Play an active role in driving product development, not only Proof of Concepts (PoCs).

• Stay up-to-date with the latest trends and techniques in machine learning, artificial intelligence, and cloud technologies.

Requirements

• Master's or PhD in Computer Science, Mathematics, Statistics, or a related field.

• 5+ years of experience in machine learning and artificial intelligence.

• Strong programming skills in Python and basic knowledge of OOP concepts.

• Proficient with SQL.

• Experience building and deploying machine learning models in a production environment.

• Experience with cloud technologies such as Google Cloud Platform.

• Strong understanding of statistical modeling techniques and data analysis methods.

• Excellent communication skills and ability to collaborate effectively with cross-functional teams.

• Ability to work independently and manage multiple projects simultaneously.

• Experience with Agile methodology is a plus

Nice to have:

• Experience with GenAI (RAG, Agents, LangChain, various LLM providers, fine-tuning, RL).

• Implementing and adhering to code review best practices.

• Writing basic unit tests in Python

Location

Krakow/Hybrid

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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.