Senior Data Scientist

The Data Science Team You will be part of the data science team. We work cross-functionally with other teams to bring data-driven impact to Aperture Cloud and its business units like Product Growth, User Acquisition and Finance. Practically the team handles 3 data areas: Data Project Management: Based on business needs, we sort requests, refine requirements and ACs with business and/or data stakeholders, prioritise, plan and executive while communicating proactive and frequently to ensure visibility and a well connected feedback loop with involved parties (reviewer, data stakeholder, business stakeholder) Applied Analytics & Data Science: Data Exploration, Defining appropriate and agile analytics approach. We aim for simplicity and interpretability but don't shy away from complexity when faced with it. All new projects have a strong Data Science component during the first MVP iteration Analytics Engineering: Data Modelling and Transformations to serve build, maintain and scale our Analytics Pipelines. Practically, as soon as an MVP gets validated by different stakeholders, we start implementing it and improving it iteratively in our dbt project. Testing and data observability is a highly important component. Proper architecture that helps manage TechDebt is another key element here as well. All members of the team are expected to excel in all three areas to be autonomously impactful. We work in an agile manner by splitting bigger projects into iterations that rarely expand beyond 3 weeks to ensure impact. We have a modern cloud-based Data-Stack (Fivetran - Big Query - dbt - Amplitude - Metabase - Looker Studio) and want to consolidate our ranks with a capable well-rounded Senior Data Scientist who can integrate our agile context smoothly and bring value quickly. Expectations | Duties This role is highly critical to the continuous success of the data science team: You will work on diverse high priority business projects to make Aperture Cloud more data driven. Those projects will be in close collaboration with business teams and will aim for clear and tangible business impact like (improving accuracy of metrics, analytically exploring new growth perspectives, building well-tested analytics reporting pipelines, investigating and correcting data discrepancies, applying statistics and ML effectively...) You will be responsible for contributing effectively to our code base: building, testing, reviewing and maintaining solid analytics pipelines using SQL and dbt. Help managing TechDebt and improving engineering practices and the project's architecture are also important responsibilities for this role. You are expected to gradually own some aspects of the team's responsibilities (some parts of the code base, become the main point of contact with at least one business team, have a strong saying in how the analytics project's architecture should evolve, contribute to team's evolution and continuous growth...) You will be expected to speak up your mind and contribute proactively and effectively to improving the team's practices, cohesion, impact and mission You are expected to be highly autonomous and show a sense of ownership and ability to effectively manage your own projects and stakeholders. This should be fulfilled with minimum guidance from the Head of Data & Analytics You will help mentoring more junior members and sharing knowledge and practices within the team to level up everyone's skills You are expected to contribute effectively to our functional documentation in a way that is clear, concise and useful for future collaborators and readers Requirements University Degree in Engineering, Computer Science or Applied Mathematics A minimum of 4 years of experience in applied Data Science with strong engineering component At least 2 years of previous hands-on experience with Digital Marketing/User Acquisition (aka UA) (attribution, iOS privacy & SKAN, UA metrics reporting) or Product/Growth (AB-testing, Retention, Monetisation...) Excellent SQL skills with previous experience building data models for analytics purposes using dbt or a similar data transformation tool that emphasises on good engineering practices and system architecture Excellent Engineering skills (testing, clean coding, peer-reviewing, CD/CI, git workflows, agile workflows, etc…) Self-Starter with the ability to work autonomously and own and manage your projects fully (also manage your stakeholders and the communication with them) Excellent written and verbal communication skills (English) Comfortable in a remote work environment (we are a remote-first organisation) Prior experience with some of the tools we use in our Data-Stack (Amplitude, dbt, BigQuery, Metabase) - or similar ones Prior experience in an agile start-up environment Benefits About Us An award-winning health, wellness, & coaching company that creates apps which fall the top ten internationally. Our science-based approach sits squarely in the tech-for-good lane, helping people live their best