Data Scientist

1 week ago

Stockholm, Sweden emagine Consulting Full time

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.


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

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