Senior/Staff Data Scientist

Summary

Join Platform Science as a Senior/Staff Data Scientist to lead the evaluation, design, and implementation of machine learning models and statistical analyses to support key business objectives.

Requirements

• 5+ years of experience in a data role, with at least 4 in a data science role
• 2+ years of experience with reporting and visualization tools such as Looker, Tableau, Domo etc
• Experience in mentorship or leadership roles, with the ability to provide guidance and support to mid-level data scientists
• Deep understanding of machine learning libraries (scikit-learn, tensorflow, etc.) and algorithms
• Advanced knowledge of statistics and experience using statistical packages for analyzing datasets (Python, numpy, pandas, R, etc.)
• Experience with experimental design and determining the statistical significance of analyses
• Experience with AWS’s data services such as Sage Maker, S3,  EC2, Lambda, etc
• Expert SQL skills including multiple-table joins, unions, sub-queries, CTE, aggregations, temporary tables, and analytical functions
• Strong analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy
• Ability to take vague requests and transform them into concise deliverables at a level of detail appropriate to the target audience, with attention to detail and accuracy
• Demonstrated expertise in establishing machine learning pipelines from scratch
• Excellent communication skills, both verbal and written
• BS in Data Science, Statistics, Mathematics, Economics, Computer Science, Information Management or equivalent experience

Responsibilities

• Conduct comprehensive evaluation of ML opportunities and summarize findings and recommendations to address business use cases and inform the data science strategy
• Collaborate with other Data Science team members and Product leaders to define the data science strategy and roadmap for Platform Science
• Utilize advanced data mining and machine learning techniques, such as natural language processing, deep learning, and neural networks, to solve complex business problems
• Leverage our modern data stack (dbt, Snowflake) to filter, clean, and transform data from a variety of sources
• Work closely with our product and engineering teams to help address their questions and goals with analytics and data science solutions
• Communicate findings and recommendations to stakeholders in a clear and concise manner
• Contribute to the development of the company's data science capabilities, including implementing best practices and processes
• Mentor and provide guidance to mid-level data scientists to help them grow and develop their skills

Benefits

• Medical, dental, and vision insurance
• Short-term and long-term disability insurances
• AD&D and life insurance
• 401k plan
• Paid vacation, sick leave and holidays
• Six weeks of paid parental leave