We are looking for a Staff Data Scientist to join a Growth Alliance team at the Tech Lead level. This role goes beyond hands-on data science, it requires a candidate who can set technical direction, lead complex ML initiatives, and act as a strategic partner to business stakeholders. You will operate at the intersection of advanced machine learning, real-time systems, and product growth.

About the Project:
This is a Staff / Tech Lead position within a team driving AI-powered decisioning at scale. You will work on systems with strict real-time constraints (<40 ms latency) that directly impact end-user experience and conversion. The mission is to move the product toward AI-driven decisioning, targeting a measurable improvement in conversion (~5%). You will be expected to challenge assumptions, define the technical roadmap, and ensure that ML systems perform reliably in production.

Responsibilities:

Lead the design and implementation of production ML systems, including real-time decisioning and personalization engines;
Drive adoption of contextual bandits, uplift modeling, and advanced recommendation frameworks;
Define experimentation strategy including A/B testing, causal inference, and synthetic controls;
Oversee feature engineering at scale and ensure robust model monitoring and validation practices;
Act as a technical owner for decisioning platforms and Martech integrations;
Collaborate with and influence senior business stakeholders to shape data science strategy;
Guide and mentor other data scientists on the team;
Lead GenAI and LLM-based initiatives including fine-tuning, evaluation, and content personalization.

Qualifications:

10+ years of experience in Data Science, with a strong track record in production ML systems;
Expert-level Python (NumPy, Pandas, Scikit-learn) and SQL;
Deep experience with PySpark / Apache Spark for large-scale data processing;
Mastery of gradient boosting methods (XGBoost, LightGBM), recommendation systems, NLP, clustering, and uplift modeling;
Extensive experience with A/B testing, causal inference, statistical modeling, and synthetic controls;
Proven ability to build and maintain production ML pipelines on cloud platforms (AWS preferred);
Experience with decisioning platforms, personalization engines, and Martech integrations;
Hands-on experience with LLMs, prompt engineering, evaluation, and fine-tuning;
Strong stakeholder management skills with the ability to challenge assumptions and ask the right questions;
Databricks experience is a nice to have.

Recruitment Process:

Initial interview with our recruitment team;
Interview with the hiring manager;
Live Coding Assessment;
Meeting with the Project Manager.

Inuits Sp. z o.o. is registered in the National Register of Employment Agencies (KRAZ) under number 35420.