10210-1 Data Scientist, Customer Service AI

10210-1 Data Scientist, Customer Service AI

We are supporting a global tech organisation.

This is a freelance contract for 6 months initially, with a view to extend
The rate is up to €110 per hour (+ VAT), it is 40 hours per week
2 days per week in the Amsterdam office

Data Scientist, Customer Service AI
We are extending our AI capabilities in Customer Service at and are looking for a Data Scientist who is passionate about turning data into meaningful insights and measurable business impact.
You will explore large-scale datasets, design and evaluate experiments, and work closely with cross-functional teams to shape how AI improves customer and partner experiences. You should be comfortable working independently, communicating clearly with both technical and non-technical audiences, and driving projects from exploration to measurable outcomes.

What you’ll do:
Conduct data exploration and visualization to uncover insights that guide AI and operational decisions.
Design, analyze, and interpret A/B tests and other experimental setups.
Measure the impact of AI solutions and communicate findings to stakeholders.
Collaborate with Product, Engineering, and Operations to turn insights into scalable improvements.

What we’re looking for:
Strong experience in Python for data analysis and modeling.
Hands-on experience with Databases (especially Snowflake) and PySpark for large-scale data processing.
Knowledge of Causal Inference and experimental design techniques.
Excellent communication and storytelling skills.
Independent, proactive, and comfortable working in fast-paced environments.
Responsible for owning the design and delivery of entire Data Science solutions based on business requirements, bringing them from the initial idea-generation phase to implementation independently.
Responsible for working autonomously on consuming data, preparing it for data science use, translating business problems to data stories and solving them effectively by applying suitable statistical data analysis and modeling methods. Leverages input from business stakeholders in all of the above to determine the right technical solutions to deliver customer value.
Responsible for working primarily within the scope of their team to deliver work that informs business decisions for the product / business topic they currently work on, occasionally collaborating across multiple teams.
Responsible for designing and interpreting quantitative experiments to objectively guide key business decision making.
Responsible for independently identifying and managing stakeholders in operational, project-based, and managerial roles. Effectively communicates, addresses stakeholder needs, and conveys complex analysis results in a clear manner. Begins to guide junior colleagues in stakeholder engagement.
Responsible for being flexible in adopting existing internal and external Data Science approaches, proposing and spotting opportunities to apply new approaches and expanding their technical competencies and their peer’s when a more efficient way presents itself.
Responsible for leveraging Data Science for impact while learning to incorporate scalability, reproducibility and long term orientation in their work.
Responsible for acting as a force multiplier for junior peers in the team by actively helping them with their craft through means of coaching, mentoring and setting a good example.
Responsible for contributing to the community of their area by supporting community projects aimed at making other data professional more effective, actively participating in community strengthening activities (ie. recruitment) and connecting with peers beyond their area.
Must be knowledgeable about the larger data ecosystem and how it relates to the work they do.
Responsible for collaborating with peers in related crafts (ie. Data Engineering), anticipating data needs to ensure smooth progress of their individual projects.
Must be knowledgeable with the operational, tactical and strategic goals of their area (ie. track / vertical) and have high level knowledge of the goals of their wider area (ie. Business Unit).
Responsible for ensuring quality of their own work by validating it through peer review.
Responsible for influencing business decisions within their specific area (ie. product team).

Master degree