Semi Senior Data Scientist

The Semi Senior Data Scientist will help develop solutions for digital marketing use cases using statistical, data mining methods and data engineering solutions, working closely with our Analytics, Media Account Management, and Solutions Engineering teams. The semi senior data scientist should be a data specialist with some experience in the deployment of propensity modeling, clustering analysis, churn analysis, product recommender systems and descriptive analytics. The candidate can expect to participate in all technical phases of internal research & development and client projects, including data discovery, data engineering, model development and/or data mining and evaluating options. It is also expected some participation in the organizational phases of projects such as project definition, tasks planning and estimation, making recommendations for the client.ResponsibilitiesNurture client understanding of the importance of building & testing data-driven strategies. Use predictive modeling to increase and optimize customer experiences, revenue generation, ad targeting and other business outcomes.Use statistical analysis and machine learning libraries (R Stats, Python StatsModels, scikit-learn, etc.) to create models that quantify the influence of online activities on offline conversions.Deploy cloud resources (Microsoft Azure, AWS, GCP or other) to perform analysis on large data sets.Create ML pipelines models from data-wrangling to getting it into production.Utilize data visualization techniques to explain data and models to clients and internal teams (Power BI, Tableau, Looker, etc.).Mine data to support analytical projects and prepare data to support the development of information models to prove or disprove project hypotheses.Design and manage experiments to ensure proper execution, data cleanliness, and statistical significance of results.Act as a consultative resource to help clients understand the quality of their internal testing processes.QualificationsEducational background in Computer Systems, Mathematics, Statistics or PhysicsProven experience articulating, translating, and solving business problems through data.Work experience in cloud vendors (GCP, AWS, Azure).2+ years of experience in data science (statistical modeling, machine learning for forecasting, classification and optimization)Experience analyzing large data sets with the Python or R data ecosystem.Experience using large databases (SQL, Snowflake, BigQuery or similar).Experience using Power BI, Tableau, Looker, or similar.Experience leveraging digital analytics (Google/Adobe Analytics) and measurement solutions data in the digital advertising industry.Willingness to both teach others and learn new techniques.Advanced English communication skills. This will be tested during the selection process.Preferred qualificationsA set of certifications or work experience in another cloud vendor (GCP, AWS, Azure).Hands-on experience in model deployment, governance, and workflow optimization (MLOps).Hands-on experience with cloud orchestration tooling, infrastructure-as-a-code.Hands-on experience building scalable ETL pipelines (Apache Beam, Airflow, Cloud Composer, Cloud Functions, Pub/Sub).Ability to explain the analytical methods and results to non-technical stakeholders to drive data-driven decision making.We are an equal-opportunity employer committed to building a respectful and empowering work environment for all people to freely express themselves amongst colleagues who embrace diversity in all respects. Including fresh voices and unique points of view in all aspects of our business not only creates an environment where we can all grow and thrive but also increases our potential to produce work that better represents—and resonates with—the world around us.

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