Overview
Job Description for Data Scientist
Development experience in one or more object-oriented programming languages (e.g. Python, Java).
Experience working closely with other data scientists, data engineers, software engineers, data managers and business partners.
Can build scalable, re-usable, impactful data science products, usually containing statistical or machine learning algorithms, in collaboration with data engineers and software engineers.
Can carry out data analyses to yield actionable business insights.
Hands-on experience (typically 5+ years) designing, planning, prototyping, productionizing, maintaining, and documenting reliable and scalable data science products in complex environments.
Applied knowledge of data science tools and approaches across all data lifecycle stages.
Thorough understanding of underlying mathematical foundations of statistics and machine learning.
Development experience in one or more object-oriented programming languages (e.g. Python, Java).
Strong software engineering and ML system design experience.
Advanced SQL knowledge.
Customer-centric and pragmatic mindset. Focus on value delivery and swift execution, while maintaining attention to detail.
Need candidate with very strong communication skills (including written).
Responsibilities
- 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 and mentor others if needed
Qualifications
Essential
Hands-on experience (typically 2+ years) designing, planning, prototyping, productionizing, maintaining and documenting reliable and scalable data science products in complex environments.Applied knowledge as part of a team (if not leading) of data science tools and approaches across all data lifecycle stages.Thorough understanding of underlying mathematical foundations of statistics and machine learning.Development experience in one or more object-oriented programming languages (e.g. Python, Go, Java, C++)Basic SQL knowledge.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.Continuous learning and improvement mindset.Desired
Experience with big data technologies (e.g. Hadoop, Hive, and Spark) is a plus.Knowledge of experimental design and analysis is a plus.No prior experience in the energy industry required.MSc or PhD degree in a quantitative field. Preferable#J-18808-Ljbffr