Data Scientist

Overview

In this role you will help build and improve Tripledot’s experimentation analytics platform. You’ll work with Data Engineering to define statistical logic, prototype methods in Python, and ensure reliable, accurate metrics for product teams across our portfolio. Early duties include hands-on QA, validating platform outputs and researching discrepancies, with opportunities to expand into advanced statistics and machine learning. You’ll collaborate with cross-functional teams to drive data-driven decisions and platform quality, making a tangible impact on game development at scale.

Pay / Benefits

• 25 days holiday
• Hybrid working
• Daily free lunch
• Employee Assistance Program
• Private medical cover
• Pension plan

Responsibilities

• Define statistical logic and requirements for experimentation features
• Prototype methods and analyses in Python before implementation
• Collaborate with Data Engineers to build and enhance the experimentation platform
• Perform data and feature QA by independently calculating results and comparing with platform outputs
• Investigate discrepancies, identify root causes, and ensure metrics are reliable
• Explore opportunities to automate QA processes and improve validation quality
• Develop deep understanding of experimentation methodologies including A/B testing, monitoring, segmentation
• Collaborate with BI, ML, and product teams to shape effective solutions
• Contribute to future statistical, algorithmic, and ML initiatives as priorities evolve

Key requirements

• 3-5 years of professional experience as a Data Scientist or in a related role
• Strong Python skills for prototyping and scripting
• Solid knowledge of statistics and standard statistical methodologies
• Practical understanding of experimentation and A/B testing, including metric calculation and validation
• Familiarity with machine learning methods and applicability to problems
• Excellent attention to detail and disciplined QA approach
• Strong problem-solving and process-improvement mindset
• Clear communication to explain methods, results, and rationale
• Experience with high-volume digital products or experimentation platforms would be valuable
• Experience using AI-assisted tools to accelerate data exploration and prototyping

• attention to detail
• problem-solving
• clear communication
• Python
• Statistics
• A/B testing

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