Principal Data Scientist

Description

Enphase Energy is a global energy technology company and leading provider of solar, battery, and electric vehicle charging products. Founded in 2006, Enphase transformed the solar industry with our revolutionary microinverter technology, which turns sunlight into a safe, reliable, resilient, and scalable source of energy to power our lives. Today, the Enphase Energy System helps people make, use, save, and sell their own power. Enphase is also one of the fastest growing and innovative clean energy companies in the world, with approximately 68 million products installed across more than 145 countries.     

We are building teams that are designing, developing, and manufacturing next-generation energy technologies and our work environment is fast-paced, fun and full of exciting new projects.     

If you are passionate about advancing a more sustainable future, this is the perfect time to join Enphase!    

About the role

For our Customer Experience team, we seek Hands-On Principal Data Scientist who can work on designing & implementing high quality scalable AI/ML applications and platforms, while providing technical leadership/mentoring to a small team of talented developers in agile environment. Your ability to lead the architecture, design, and implementation of maintainable, high-quality, and high-performing Machine Learning systems and AI applications is essential for success in this role.    

Provide hands-on technical expertise to design, engineer, deploy, and deliver highly scalable machine learning applications. Drive improvements in technical architecture, standards, and processes. Drive engineering excellence while managing/mentoring talented team of developers in agile environment. Work closely with product management and other stakeholders for system design and delivery.    

What you will do:    

• Understanding the customer experience business use cases and technical requirements and being able to convert them into a technical design that elegantly meets the requirements
• Come up with solutions for Data Science business problems, implementation, and review code
• Come up with use cases and accelerators. Understand business problems and propose solutions. Guide team with best practices. Design solutions on cloud and on-premises and present solutions to clients
• Responsible for the architecture and design of data science platforms & service capabilities by envisioning and executing strategies that will enable and leverage modern data science capabilities
• Implementation of sophisticated analytics programs, machine learning, and statistical methods to prepare enterprise data for use in predictive and prescriptive modeling
• Accountable for the data science platform design in addition to the use of case-based application solution design
• Work on complex unstructured datasets using advanced statistical and analytical methods
• Lead the company’s AI efforts to develop intelligence in all of the key areas of interest
• Work independently and have ability to identify highest impact problems
• Work closely with other technical and operational functions to gather, organize and analyze datasets to extract meaningful insights

Who you are and what you bring:

• MS or Bachelors in Computer Science, Math, Machine Learning, or a relevant field with 12+ yrs. of experience in industry and/or academic research
• Strong Experience in Python for Data Science, Data Science on AWS, Data Science solutions, Communication and Collaboration, Statistics & Probability
• Ability to design and implement workflows of Linear & Logistic Regression, Ensemble Models (Random Forest, Boosting) using R/Python
• Demonstrable competency in Probability & Statistics, ability to use ideas of Data Distributions, Hypothesis Testing, and other Statistical Tests
• Demonstrable competency in Data Visualization using the Python/R Data Science Stack
• Hands-on experience in using statistical and analytical techniques to complex business problems
• Hands-on experience in solving regression, prediction, classification, clustering, neural networks, and Bayesian problems
• Advanced knowledge of statistical techniques, machine learning algorithms, Bayesian Models, data mining, and text mining
• Experience in handling large datasets on cloud and on-premises setup, using distributed computing
• Able to understand various data structures and common methods in data transformation
• Strong Programming background and expertise in building models in languages like Python, R, Scala, etc.
• Good knowledge of visual techniques for data analysis and presentation skills
• Strong troubleshooting skills in different disparate technologies and environments
• Enthusiastic about different areas of work and exploring new technologies
• Clarity of thought and strong communication skills to effectively pitch solutions
• Ability to explore and grasp new technologies
• Mentoring your team members in projects and helping them keep up with new technologies
• Empowering the team members to be solution providers and enable a flat environment where every ones point of view is considered, and feedback is encouraged