The ideal candidate has a track record of having built multiple high-performance, stable, scalable systems that have been successfully shipped to customers in production. Your work and your approach to work are exemplary: you drive best practices and set standards for your team.  You are a key influencer in your team’s strategy and contribute significantly to team planning. You show good judgment in making trade-offs between immediate and long-term business needs.  You are a collaborative leader that makes other engineers and team members around you more productive, by sharing your knowledge, and helping to tie-break key technical decisions. You provide mentoring to other scientists and engineers.

Start: ASAP

Duration: Min 7-8 months

Location: Mostly remote but must be from Sweden and preferably from Stockholm


The perfect candidate will have a background in a quantitative or technical field, will have experience working with experimentation on large data sets, strong statistics, analytics and will have experience in data-driven decision making and machine learning. You are focused on results, a self-starter, and have demonstrated success in using analytics to drive the understanding, growth, and success of a product.

 

If you delight in data science and use the latest in AI/ML/RL to help use data to make and drive decisions for hundreds of millions of customers across web, mobile and connected devices, then this is the role
for you.

 

What to bring

  • Expert in Python language.

  • Expert in Python Notebooks Data Science Libraries (Scipy, Numpy, Pandas, Scikit-learn)

  • Asynchronous, non-blocking, functional style of programming and experience implementing with Python.

  • Strong SQL & NoSQL experience and performance tuning.

  • Expert in Databricks Platform (SQL, Compute, Clusters, ML, Workflows)

  • Strong DBT (Data Build Tool) experience in building and architecting data pipelines and analytics workflows. Including unit testing and data testing of DBT based SQL & Python models.

  • Experimentation design and A/B testing

  • Expert knowledge of statistical analysis. Including P-value, T-Test, Lift calculations for experimentation analysis.

  • Experience in machine learning and reinforcement learning systems (ML/RL) and building ML models, ML operations and feature engineering. Including related tooling for shared feature stores, release and deployment management.

  • Experience of Exploit vs Exploration problems and related Bandit algorithms for Experimentation.  Including Contextual Multi Armed Bandits, Epsilon-*, Search, Ranking, Markov Chains, Attribution, Decision, Thompson Sampling and other families of algorithms to help solve problems.

  • Experience working in fields of quantitative analysis, machine learning, modeling, statistics, attribution (Shapley, Markov), research and algorithm development.

  • Demonstrated ability to work in a highly collaborative way on large scale projects.

  • Excellent communication skills both written and verbal

  • Required MS Degree or PHD in Computer Science, Maths, Statistics or equivalent experience

  • Designing and evaluating experiments, monitoring key product metrics, understanding root causes of changes in metrics

  • Understanding of causality and its effect on machine learning applications

  • Collaborate with data and analytics engineers assisting on data work.

  • Offer enhancements to best practices and documentation.

  • Building and analyzing dashboards and reports. Looker (Google) dashboard experience would be ideal.

  • Exploratory Analysis & Research