WHAT YOU BRING:

Must-Haves

• Excellent SQL skills and outstanding analytical abilities.
• 3+ years of experience in data analytics, ideally in retail or consumer products.
• Hands-on experience with Python (Pandas, Numpy, Matplotlib) or R.
• Strong communication skills in English, with the ability to explain data concepts to non-technical audiences.
• Degree in computer science, data science, mathematics, statistics, physics, economics, or a related field.

Nice-to-Haves

• Experience with big data environments (e.g., PySpark).
• Familiarity with statistical modeling or behavioral price effects.
• Additional languages beyond English.

ABOUT THE ROLE:

At Centric, we help some of the world’s most recognized fashion, beauty, and home brands make smarter pricing and inventory decisions with the power of AI. As a (Senior) Data Scientist / Consultant, you’ll combine deep analytical expertise with a consulting mindset — applying advanced data techniques while working directly with clients to turn insights into measurable impact.
This role is ideal if you enjoy problem-solving, explaining complex concepts clearly, and collaborating with international teams to deliver innovative solutions.

WHAT YOU’LL DO:

Customer & Project Engagement

• Partner with project managers, consultants, and clients throughout onboarding projects.
• Translate business processes and customer requirements into actionable data transformations and modeling approaches.
• Communicate technical concepts to non-technical stakeholders in a clear, approachable way.

Data & Model Ownership

• Serve as the technical point of contact for data science and data engineering topics.
• Ensure accurate, stable, and well-documented data flows (incoming and outgoing).
• Design, prepare, and analyze A/B test setups.
• Train and validate statistical and machine learning models to quantify the impact of pricing and promotions.

Collaboration & Delivery

• Work closely with product management to prototype and implement ideas into efficient, well-tested code (R and Python).
• Track project-specific effort and ensure solution documentation is reliable and complete.
• Interface with customers and partners to align on data formats and transmission schedules.