We are seeking a talented and motivated Data Scientist to join our team. The ideal candidate will have a strong background in data analysis, predictive modeling, and machine learning, and will be excited to apply these skills to solve complex problems and generate insights that drive our business strategies. This role will involve working with large datasets, developing predictive models, and collaborating with various teams to deliver data-driven solutions, particularly within the energy sector.
What we offer Interact with senior stakeholders on regular basis, to drive their business towards impactful change.Become the go-to person for end-to-end data handling, managementand analytics processes.Work with Data Engineers to take data throughout its lifecycle - acquisition, exploration, data cleaning, integration, analysis, interpretation and visualization.Become part of a fast-growing international and diverse team. What you will do You own together with your team several of our Data Science solutions throughout the full life cycle (brainstorming, design, implementation, productization and maintenance)Analyze large datasets to identify trends, patterns, and insightsDevelop, implement, and maintain predictive models and machine learning algorithmsCollaborate with cross-functional teams to understand business requirements and translate them into data-driven solutions.Create effective data visualizations to communicate findings and recommendations to both technical and non-technical stakeholders.Evaluate and improve model performance through validation techniques and hyperparameter tuning.Stay updated with the latest trends and advancements in data science and machine learning What you'll bring Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, Engineering, or a related field. A PhD is a plus. Minimum of 3 years of experience in a similar Data Scientist role. Strong programming skills in R (Python is a plus). Knowledge of predictive modeling techniques, time-series analysis, regression analysis, clustering, classification, and dimensionality reduction. Experience with machine learning tools and libraries (Spark). Proficiency in SQL and database management systems (e.g. Databricks, Snowflake). Ability to manipulate and analyze large datasets using tools such as Pandas, NumPy, and other data analysis libraries. Experience creating visualizations using tools like Matplotlib, Tableau, or Power BI. Excellent communication skills and the ability to work collaboratively in a consultancy environment. Preferred skills: Familiarity with cloud services, particularly Azure and Azure Functions. Knowledge and experience with dbt and GitHub. Experience deploying models in production environments.
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