Principal Data Scientist - AI

Welcome to GEP

Who We Are

GEP, with over 30 offices internationally, is the fastest growing procurement and supply chain solutions firm – consulting, software and managed services. GEP has succeeded by being smart and creative; solving complex problems and finding opportunities for the world’s largest organizations.

How You Grow At GEP

We recognize people who make a genuine difference, work hard and drive achievements. Results are noticed and rewarded. It’s how you will grow a career at GEP, and in a much shorter time frame than at other firms.

Celebrating Everyone

GEP succeeds through the ideas and creativity of our team members so we embrace people of all experiences, nationalities, abilities, cultures, races, gender identities, sexual orientations and ages. What makes you unique and different is celebrated and will help GEP stand out even more. And we are a women-founded and -owned company so our foundation is making GEP a great place to work for women, a place where women can learn, advance and give back.

What You Will Do

As a Data Analytics Coordinator at GEP, you will lead the development of advanced analytics, data science solutions, and data products that transform complex data into scalable business value. You will combine people leadership, analytical depth, product thinking, and strong business acumen to ensure solutions are technically robust, reusable, measurable, and aligned with client and business needs. You will:

• Lead and develop the Data Analytics team, ensuring clear priorities, technical quality, delivery predictability, and continuous development of team members.
• Translate business problems into analytical solutions, selecting the right approach across descriptive, diagnostic, predictive, and prescriptive analytics.
• Lead the design and development of statistical, econometric, machine learning, forecasting, segmentation, scoring, and optimization models.
• Drive the development of data products, transforming recurring analytical needs into scalable, reusable, and sustainable solutions.
• Define the vision, roadmap, target users, value proposition, success metrics, and lifecycle of analytics and data products.
• Ensure appropriate validation, backtesting, performance monitoring, recalibration, documentation, and governance of models and analytical solutions.
• Partner with Data Engineering, Data Governance, Product, Market Intelligence, and business teams to ensure reliable, traceable, and high-quality data foundations.
• Identify opportunities to convert ad hoc analyses, recurring requests, and manual processes into standardized analytical products or automated solutions.
• Establish standards and best practices for analytical development, reusable datasets, business rules, metrics, documentation, and model lifecycle management.
• Monitor KPIs related to model performance, product adoption, data quality, business impact, usability, and value generated by analytics solutions.
  
  

What Should You Bring

• Bachelor’s or Master’s degree in Data Science, Statistics, Economics, Computer Science, Engineering, Mathematics, or another quantitative discipline.
• Expertise in Data Analytics, Data Science, Advanced Analytics, or related fields.
• Knowledge leading people, projects, or analytical workstreams, with demonstrated ability to develop others and drive delivery.
  
  

Technical, Product and Leadership Skills

• Strong proficiency in Python and SQL and solid knowledge of statistics, forecasting, time series, regression, hypothesis testing, and predictive modeling.
• Expertise with machine learning, model evaluation, feature engineering, backtesting, validation, and performance monitoring.
• Knowledge with cloud data platforms such as Databricks, Azure, AWS, or equivalent technologies, and understanding of MLOps and model lifecycle management.
• Strong data product mindset: ability to define users, problems, business value, roadmap, success metrics, adoption criteria, and lifecycle of analytical products.
• Ability to distinguish ad hoc analysis from scalable data products and identify opportunities for reuse and standardization of datasets, metrics, models, and analytical components.
• Understanding of data quality, ownership, SLAs, documentation, lineage, governance, and data architecture principles from an analytics product perspective.
• Proven ability to connect technical solutions with business outcomes and communicate complex concepts to technical and non-technical stakeholders.
• Strong people leadership, coaching, prioritization, stakeholder management, and structured problem-solving skills.
• Advanced to fluent English, with the ability to communicate effectively with global teams and stakeholders in meetings, presentations, and day-to-day collaboration.
  
  

At GEP, Data Analytics Coordinators connect people, data, technology, and business — helping analytics evolve from individual analyses and models into scalable capabilities and products that support better decisions for our clients and our organization.

Are you one of us?

GEP is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, ethnicity, color, national origin, religion, sex, protected veteran status, disability status, or any other characteristics protected by federal, state or local law. We are committed to hiring and valuing a global diverse work team. GEP is proud to be an EEO/AA employer M/F/D/V. Show more Show less