SphereOI helps clients succeed with advanced data analytics. Our custom framework creates purpose-driven competitive differentiators by linking advanced analytics technology to business opportunities and portfolio strategy. We keep the focus on what is most important as we work with clients to give them the practical skills to stand on their own in developing the future.
This position is for a Data Scientist / Machine Learning Technical Lead who will work in our studios as a Technical Lead for our data science team. The position will support multiple clients over time, crossing a broad spectrum of industries. The pace is fast, but the technology and opportunities to experiment with new approaches are exciting. The position requires a significant proficiency with statistical science in the context of machine learning. The work involves exploration, experimentation, and implementation. The more varied your background, the better. Data, big and small, is a ubiquitous element, and familiarity with modern data architecture and query languages is important. This position will, over time, draw on your skills in NLP, demand forecasting, computer vision, cyber-physical systems, and deep/reinforcement learning.
What You Will Be Doing
• Learn new domains and problems.
• Push the boundaries of ML in demand forecasting, computer vision, agent design, NLP, and other areas.
• Develop reference implementations of models and pipelines.
• Draw conclusions from data and recommend actions.
• Work in Python, possibly other languages (e.g. R, Java).
• Present at weekly demos and various sessions.
• Provide guidance and instructions to data science team, interact with a wide variety of leaders.
• Work closely with customers to explain technical solutions.
What You Need for This Position
• Talent for machine learning fundamentals < We stress the fundamentals
• An advanced degree in a quantitative discipline (Statistics, Operations Research, Economics, Computer Science, Mathematics) or equivalent practical experience.
• Hands on experience with statistical software (R, Python, pandas) and database languages such as SQL.