Senior Data Scientist

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. At the same time, 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:

Specifically, this role will function as a Senior Data Scientist in the Enterprise Data & Analytics (EDA) group with responsibility for using knowledge of data analysis, statistics, machine learning, and predictive modeling to leverage AutoML tools and build custom solutions to support key initiatives with a commitment to innovation and value creation.

The key areas of focus for this role include building advanced analytics capabilities, creating strategic roadmaps for projects involving AI/ML with business stakeholders and pods in the EDA group, partnering with the BI engineering team to build visualizations that use inputs/outputs of the models, and driving self-service capabilities to enable real-time information and predictive insights at scale across the organization by leveraging technology paved paths, reference architecture, design patterns, and industry best practices.

This individual must be a technologist & analytics engineer at heart and be comfortable enabling new technology and being hands-on with the execution of the strategy. In addition, they must exhibit a deep understanding of industry technology trends and the ability to stay current with the competitive landscape, modern technology stacks, and agile delivery models with a demonstrated focus on customer experience.

This individual will partner with senior leadership, team members in the EDA group, business stakeholders, and domain teams in technology by providing thought leadership to support technology roadmaps and delivery commitments. In addition, they will be responsible for cultivating a data-driven culture by elevating our maturity in analytics to enable decision making to drive growth, optimize operations, and improve customer experience. As such, it will be imperative to build and maintain strong relationships and demonstrate organizational savvy. Demonstrated experience explaining complex concepts with insightful narratives to executive leaders and excellent presentation skills are also required.

Position Responsibilities:

25% - Strategy & Planning:

Partner with stakeholders to drive product development, strategic projects, and other delivery commitments

Deliver consultation to the functional areas in the business on best practice uses of AI/ML tools and offer recommendations on ways to enhance/enrich their models and frameworks

Influence across teams to align resources and direction

25% - Analytics Enablement & Evangelism:

Partner with teams to create a data-centric organization by fostering data literacy, information literacy, visualization literacy, and technology literacy

Drive adoption (new users) and increase usage (existing users) of platforms + tools

Ensure that results from initiatives are operationalized and communicated so stakeholders maximize their value at all levels

50% - Delivery & Execution:

Collaborate with analytics pods in the EDA group, business stakeholders, product management team, domain (application development) groups, and other groups to identify use cases for data science projects

Manage value streams and the evolution of ML models and software components that deliver state-of-the-art data science solutions from end-to-end (intake, requirements gathering, design, development, QA, UAT, deployment, training, enablement)

Serve as a technical expert on each component of the analytics pipeline (data modeling, exploration data analysis, feature engineering, AI/ML techniques, model evaluation, model selection, and visualization) for initiatives involving data science

Conduct exploratory analysis including hypothesis testing, statistical inference, and statistical analysis

Develop processes and tools that monitor, analyze, and continuously improve model performance and data accuracy

Assess and recommend new tools, technologies, and external partnerships that can enhance the organization's data science and analytics capabilities

Publish, educate, and secure acceptance of complex mathematical concepts (statistics, linear algebra) and models from various stakeholders

Aid the EDA group team in establishing project ROI’s, documenting business outcomes, and tracking benefit realization

Other duties as assigned

Desired Qualifications & Experience:

Bachelor’s degree in related field or equivalent experience

Masters of Science in Analytics from an accredited institution (or other advanced degree in computer science, MIS, or business intelligence) preferred

2 years of experience (7-10 years preferred) working in a Data Scientist role with proven track record of using knowledge of data analysis, statistics, machine learning, and predictive modeling to leverage AutoML tools and build custom solutions to support initiatives

Demonstrated and advanced proficiency with programming languages (Python, PySpark, R) and developing custom scripts that execute analytics pipelines using large data sets spanning various levels of complexity and curation (raw data to semantic views)

Strong knowledge of machine learning algorithms, including unsupervised (clustering, dimension reduction, association, recommendation systems, graph), supervised (classification, linear regression, decision trees, random forests), deep learning (CNN/GNN/RNN), and reinforcement learning

Expertise on best practices related to techniques, methods to use, benefits/limitations of each, and performance improvement options through hyperparameter optimization

Experience developing, selling, and sharing modeling concepts to key stakeholders, including executive leaders, with a focus on using explainable AI (xAI) methods to drive adoption and implementation

Demonstrated proficiency with cloud data platforms at an enterprise level and strong knowledge of SQL; preferably Google BigQuery (including BigQuery ML, BigQuery Studio)

Demonstrated proficiency with BI tools; preferably Power BI

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.

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