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 Fabulous 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 Fabulous 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 lives. Everyone who has joined this company is committed to using evidence-based research to find the absolute best ways to change lives for the better.

Our History

Three co-founders created the Fabulous app: Sami, Amine, and Taylor. Growing up in Tunisia, Sami and Amine were only 16 when they met. With their early iteration, they reached out to Taylor, an award-winning designer in Malaysia. Their vision was welcomed into an incubation lab for startups at Duke University led by world-renowned Behavioral Economics Professor Dan Ariely. Our Chief Storyteller Jaz co-founded the Introductory Psychology program at Stanford University.

Our Approach

We use a behavioral economics lens to help individuals find that 'on switch' inside them to achieve their fullest potential. What has emerged is a system that transforms tiny habits into profound long-term changes. A world in which people with ADHD thrive. A method for gratitude to reach through difficulty. A sanctuary to seek out your true purpose. A fountain of knowledge. A space for rest and self compassion.

Our Mission

Help every individual discover the wonderful person inside themselves by creating: beautiful, evidence-based, life-changing products.

Our Environment

The first thing that sets us apart is that we’re not a place at all. While we’re a remote company, it’s not unusual to feel you know your teammates better than those you’ve shared an office with in the past. Ours is a professionally nourishing environment that is flexible and fully remote. Team members enjoy in house challenges and Slack event and work across a variety of tools. Meetings are kept to a minimum and deep work is encouraged.

Our Awards

• Apple Best Apps of 2018
• Editor’s app choice in more than 30 countries
• Winner of Google’s Material Design Award
• Best App Finalist in Google Play Awards
• Consistently ranking in the top ten Health & Fitness apps
• Backed by Facebook Startup Lab and Microsoft Venture

Our Norms

Ownership: Be the CEO of your tasks. No one is watching over your shoulder. Be the proof.

Open Communication: Constructive ideas are always flying across time zones.

Deep Work: Disconnect. Find your flow. Become industrious. It’s about the work here.

Always Offer Context: Sharing rationale works wonders in asynchronous conversations.

Impeccable Agreement: Promise, then follow through. Everyone relies on everyone.

Egos are checked at the door. Those who join our workforce place themselves in service of our members.

Our Values

#collaboration #craftsmanship #feedback #respect #responsibility #simplicity #speed

Our Future

To this day, over 30 million people have started their journey to better themselves with our apps. We are creating a generation of change-makers, with the same drive to help others, each in their own way.

Our Invitation

At Fabulous, every team member is a sculptor in their own right. Together, we help millions of users step out of their block of stone and step into the fullest version of their life through behavioral science. Tell us what drives you; if you were to pick up your tools, what would you contribution look like?