Senior Data Scientist (8+ years)

data scientist applies scientific methods, processes, algorithms, and systems to extract knowledge and insights from structured and unstructured data. Their key responsibilities include collecting and analyzing large sets of data, using machine learning algorithms, statistical models, and data processing techniques to predict future trends and provide actionable insights. A machine learning engineer designs and develops artificial intelligence (AI) systems that can learn and make decisions autonomously. Their key responsibilities include creating and optimizing machine learning models, developing algorithms that enable machines to perform tasks without explicit programming, and working with large datasets to train these models. They collaborate with data scientists, software engineers, and domain experts to implement machine learning solutions that address specific business needs. Additionally, machine learning engineers are responsible for ensuring the scalability and efficiency of machine learning systems, continuously improving model performance through rigorous testing and validation, and staying updated with the latest advancements in the field to integrate cutting-edge techniques into their work.

What you will deliver

• Part of a cross-disciplinary team, working closely with other data scientists, data engineers software engineers, data managers and business partners.
• Build scalable, re-usable, impactful data science products, usually containing statistical or machine learning algorithms, in collaboration with data engineers and software engineers.
• Carry out data analyses to yield actionable business insights.
• Adhere to and advocate for data science best practices (e.g. technical design, technical design review, unit testing, monitoring & alerting, checking in code, code review, documentation).
• Present results to peers and senior management.
• Actively contribute to improve developer velocity.
• Mentor others.

What you will need to be successful (experience and qualifications)

Essential

• Bachelors / Masters / PhD degree in Computer Science, Engineering or any equivalent field.
• Hands-on experience designing, planning, prototyping, productionizing, maintaining and documenting reliable and scalable data science products in complex environments.
• Thorough understanding of underlying mathematical foundations of machine learning and deep learning.
• 7+ Years of development experience in Python programming languages
• Advanced SQL knowledge.
• Experience with Python libraries and frameworks like NumPy, Pandas, PySpark, matplotlib, Flask, FastAPI, scikit-learn, TensorFlow, PyTorch.
• Strong skills in software engineering, data processing, analytics and data visualization libraries
• Proficiency in data structures, algorithms, building and maintaining data pipelines.
• Strong problem-solving and analytical skills.
• Experience with cloud platforms such as AWS, Azure, or Google Cloud.
• Customer-centric and pragmatic mindset. Focus on value delivery and swift execution, while maintaining attention to detail.
• Strong stakeholder management and ability to lead large organizations through influence.

Desired

• Experience with big data technologies (e.g. Hadoop, Hive, and Spark) is a plus.
• Experience with GenAI Technologies is a plus.
• Knowledge of experimental design and analysis is a plus.

No prior experience in the energy sector required