Data Scientist

FairPlay Sports Media; Waterloo; On-site; GBP 60,000 - 90,000; Full time

Job summary

FairPlay Sports Media is seeking an inquisitive and impact-driven Data Scientist to join our Analytics team. You will translate complex, unstructured data into actionable strategic directions, partnering with Product, Engineering, Marketing and Operations to build predictive frameworks and uncover growth opportunities.

You will design and run rigorous A/B tests, develop predictive models for churn, forecasting, CLV, and user segmentation, and collaborate with stakeholders to turn questions into

Qualifications

• 3+ years of experience in a quantitative analytics or data science role.
• Ability to frame business problems into mathematical frameworks and output actionable recommendations.
• Strong communication to distill complex stats for non-technical executives.

Responsibilities

• Experimentation & A/B Testing: design, execute, and analyze rigorous tests to measure feature performance and business impact.
• Predictive Analytics & ML: build, validate, and maintain scalable predictive models (e.g., churn, forecasting, CLV, segmentation).
• Exploratory Data Analysis: identify trends, user behaviors, bottlenecks, growth opportunities.
• Features Definition & Measurement: standardize key features for modelling and CDP.
• Cross-Functional Strategy: collaborate with product, leadership, and stakeholders on quantitative analyses.
• Analytics AI Agents: design and manage autonomous AI agents to automate analytics tasks.
• Data Pipelines & QA: work with Data Engineering to build transformations and ensure data governance.

Skills

Advanced SQL

Python for ML

Statistics & Math

Data Visualization

Dataform

Google Analytics

Vertex AI

Tools

Snowflake/BigQuery

Job description

We are seeking an inquisitive and impact-driven Data Scientist to join our Analytics team. In this role, you won’t just build models—you will translate complex, unstructured data into actionable strategic directions that drive our core business forward. You will partner closely with Product, Engineering, Marketing, and Operations to build predictive frameworks, and discover growth opportunities.

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Key Responsibilities

• Experimentation & A/B Testing: Design, execute, and analyze rigorous A/B and multivariate tests to measure feature performance, user retention, and business impact.
• Predictive Analytics & Machine Learning: Build, validate, and maintain scalable predictive models (e.g., churn, forecasting, customer lifetime value (CLV) and user segmentation) to guide business decisions.
• Exploratory Data Analysis: Deep dive into large, complex datasets to identify trends, user behavioral patterns, operational bottlenecks, and unexpected growth opportunities.
• Features Definition & Measurement: Establish and standardize key features to track for modelling and customer data platform .
• Cross-Functional Strategy: Partner with product managers, executive leadership, and business stakeholders to turn open-ended questions into structured quantitative analyses.
• Analytics AI Agents: Design, deploy, and manage autonomous AI agents that automate repetitive analytics tasks and generate insights.
• Data Pipelines & Quality Assurance: Partner with Data Engineering to curate analytical datasets, build clean data transformations (dataform/SQL), and uphold data governance standard practices.

Qualifications & Skills

Technical Competencies

• Advanced SQL: Highly proficient in writing optimized, complex queries across large cloud data warehouses (e.g., Snowflake, BigQuery).
• Programming & Modelling: Strong proficiency in Python for statistical modeling, forecasting, and machine learning.
• Statistics & Math: Deep understanding of statistical inference, regression analysis, probability theory, decision trees, and hypothesis testing (p-values, confidence intervals, Bayesian testing etc.).
• Data Visualization: Hands-on experience building interactive dashboards using tools like Power BI, Looker, or Python libraries.

Experience & Soft Skills

• Experience: 3+ years of experience in a quantitative analytics or data science role in a fast-paced environment.
• Business Acumen: Demonstrated track record of framing business problems into mathematical/statistical frameworks and outputting actionable recommendations.
• Communication: Ability to distill complex statistical concepts into clear, plain language for non-technical executives.

Nice-to-Haves

• Experience with data building tools (i.e. Dataform) for data transformation workflows.
• Experience with digital product analytics tools (i.e., Google Analytics).
• Experience with AI Agents i.e, Vertex AI (Gemini Enterprise Agent Platform)