Data Analyst - Python, Pyspark

We are supporting global organisation.

This is a freelance contract for 6 months initially.

• 40 hours per week
• 100 EUR per hour (VAT is paid on the top)
• 2 days per week in the Amsterdam office

We are looking for a Data Analyst with strong analytical and technical skills to support data-driven decision making across cross-functional product teams.

Key responsibilities

Analyze large-scale datasets using Python and PySpark to generate actionable insights.

Design, execute, and evaluate experiments (A/B testing, holdouts) to measure product and operational impact.

Apply statistical methods and causal inference techniques to quantify true business impact and avoid misleading conclusions.

Translate complex analyses into clear insights and recommendations for product, engineering, and business stakeholders.

Partner closely with product managers, engineers, data scientists, and operations teams to support end-to-end decision making.

Proactively identify data issues, opportunities, and improvement areas, and drive follow-ups independently.

Required skills & experience

Strong proficiency in Python (pandas, numpy, statistical libraries) and PySpark for large-scale data processing.

SQL-based analytics platforms and dashboarding tools.

Solid foundation in statistics, including hypothesis testing, confidence intervals, and regression analysis.

Hands-on experience with experiment design and impact measurement.

Understanding of causal inference concepts (e.g., control vs treatment, bias, confounding, CUPED, DiD, matching, etc.).

Experience working with large datasets in data warehouses.

Strong stakeholder management and communication skills, able to explain insights clearly to non-technical audiences.

Proactive mindset with the ability to operate effectively in cross-functional teams.

Data Analysts II are the drivers for analytics tasks such as reporting, visualization and analysis needs within their area. They have a high level understanding of the business problems in their area and collaborate closely with the business stakeholders to solve them through application of data analytics. They use their experience and consultation with stakeholders in problem-definition, setting success metrics and shaping the way forward through data insights and effective communication with their audience.Data Analysts II are able to manage junior to mid level stakeholders autonomously (seeking for help with more senior stakeholders) based on their experience and practical understanding of business concepts to prioritize for business impact, efficiently adapt to business needs, and manage expectations accordingly. They combine their understanding of the business with the knowledge of data, workflows, methods and tooling to autonomously drive analysis and reporting within the scope of their team. They can find opportunities to apply new concepts and approaches into action when business and user needs demand it. They aim to deliver scalable, reproducible and long-term focused solutions in every area of their work (ie. reporting, visualization, influencing business decisions through data, etc). They collaborate, mentor peers in their team and follow best practices ensuring data quality and stability.

Key Responsibilities

Responsible for owning the design and delivery of entire Data Analytics 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 analytical use, translating business problems to data stories and leveraging input from business stakeholders 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 a product / business topic in the area they work in, occasionally collaborating across multiple teams.

Responsible for leveraging previous knowledge, experience and substantial skills in data analysis and data visualization to answer business questions in the most efficient way. They understand stakeholder needs and create intuitive and insightful visualizations that translate data into actionable insights to answer those needs.

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 Analytics 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 Analytics 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 at 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).

Level of Education

Master degree

Years of relevant Job Knowledge

Broad Job Knowledge (3 - 5 years)

Requirements of special knowledge/skills

Driven and results oriented personality

Open to feedback and always looking for ways to improve own performance

Able to understand details while keeping an eye on the bigger picture.

Able to spot opportunities to drive business growth from their craft.

Analytical and curious mindset

Strong interpersonal skills

Open and friendly attitude

Expertise and experience on data analysis.

Expertise in data management, data visualization and quality.

Expertise using data analysis and visualization tools (e.g: tableau, data studio, powerbi, mixpanel, etc)

Expertise with at least one data analysis language (e.g: R, SQL, Python, etc)