Data Scientist (Business & Product)

Medal.tv; York and North Yorkshire; Presencial; GBP 60.000 - 90.000; Jornada completa

Descripción de la vacante

Medal.tv is seeking a data-savvy analytics leader to own the end-to-end measurement strategy, instrumentation, and KPI reporting. You will design experiments, optimize multi-test pipelines, and partner with product and business leadership to turn data into strategy.

You will evangelize analytics, build data scaffolding with engineers, and publish insights that influence pricing, product roadmap, and growth initiatives. Strong SQL, Python, and statistical skills are essential.

Formación

• 3–5 years of experience managing and researching product analytics.
• Master’s degree in statistics or a related field is preferred.
• Experience with event-level data at consumer scale and data warehouse tooling.

Responsabilidades

• Design and analyze experiments end-to-end, including sample size, guardrails, control configuration, and readouts.
• Configure test structures to yield the right information and manage multi-test pipelines.
• Hunt for opportunities in data to inform strategy and business decisions.
• Communicate risks and tradeoffs in measurement vs. shipping velocity and evangelize data across teams.
• Contribute insights during planning and roadmapping and support pricing analytics where needed.

Conocimientos

SQL

Python

R

Experiment design

Causal inference

Data storytelling

Data visualization

Cross-functional collaboration

Educación

Master’s degree in statistics or related field

Herramientas

BigQuery

Snowflake

Airflow

Tableau

Amplitude

Descripción del empleo

• You’ll be part of a lean, high-ownership data team at Medal, working directly with business and product leadership
• You’ll own how we learn about our users end-to-end: the company-wide testing roadmap, our analytics instrumentation, the data pipeline, and KPI reporting, plus the deep dives and thought‑leadership publications that come out of it
• You’ll set your own roadmap, evangelize the data so everyone understands it better, and have real influence on what we build next
• Design and analyze experiments end-to-end: help affirm the team’s hypothesis and design experiment sample size, guardrail metrics, control configuration, and the resulting readout
• You will configure test structure to yield the right information and manage a complex multi-test pipeline. You know how to run causal analysis when a clean A/B test isn’t possible. You understand that multiple things will run at the same time
• You help build the strategy behind our analytics instrumentation and facilitate the collection and reporting of the company’s key performance indicators. When tracking is wrong or missing, you work with our front‑end engineers to build appropriate telemetry and data scaffolding
• You will hunt for opportunities in data that can inform strategy
• You will communicate and evangelize against the data and help everyone have a better understanding. Your recommendations include a confidence interval and effect size
• You will participate in team planning and roadmapping by contributing your insights and expertise
• You inform the quant behind pricing, including willingness to pay, conjoint, price elasticity, and offer testing in upsells and bundles
• You are the data backbone for industry and brand thought leadership (Medal trends and how they line up with macro trends), both co‑published with partners and self‑published
• Across the board, you will touch analytics and statistical analysis in a cross‑functional capacity to help inform both business decisions (advertising incrementality, subscription pricing, and conversion) and product decisions

Great communication and storytelling skillsYou are comfortable coordinating with engineers on release cycles in a CI/CD environmentStrong ability to manage your own roadmapExperience with event-level data at a consumer scale and data warehouse tooling such as BigQuery, Snowflake, or AirflowStrong SQL, Python, or R for analysis code3 to 5 years of experience managing and researching product analytics or a master’s degree in statistics or a related fieldApplied statistics depth: regression, experimental design (e.g., feature A/B tests), and causal inference. Bayesian methods are a plusYou use AI tools to enhance your productivity and raise the bar on your analysisBonus: An ability to conduct qualitative UX researchFluent in product analytics platforms like Amplitude or business intelligence tools like Tableau or tools similar to theseYou are the kind of person who asks why until why is exhaustedYou have a need for speed and are comfortable with a fast‑paced culture and a team that leans towards actionYou are the kind of person who checks whether your AI analysis is correctYou also know what the data cannot answerYou are hungry to learn and test yourself. You help level an organization upWhen you see something on the ground, you pick it upAs a custodian of analysis, you can communicate risks and tradeoffs in measurement vs. shipping velocity