Job description
A Senior Digital Product Data Scientist is a skilled and motivated data scientist who is passionate about solving real-world data science problems for ardent athletes and implementing solutions with the highest quality. Our client encourages creative solutions and strives to maintain rigorous scientific and engineering standards.
A Senior Digital Product Data Scientist works closely with product managers and business stakeholders to formulate and shape machine learning products and solutions for the purpose of making athletes better.
By delivering predictive data models, the end result of this position is three-fold: to inform better business decisions, to personalize our data product offering, to improve engagement with our client's customers and user base.
ESSENTIAL DUTIES & RESPONSIBILITIES
- In collaboration with product managers, hypothesize and formulate data science solutions that produce business insights, help make athletes better, and produce positive engagement with end users.
- Identify, develop and store input components of the model lifecycle, including ETL pipelines, feature generation, and feature selection in order to create training ready data sets.
- In the output of the model lifecycle, train, test, store, and tune predictive data models that produce business insights, help make athletes better, and produce positive engagement with end users.
- Research, compare, and incorporate current industry methodologies and patterns for data science in the digital fitness space.
- Collaborate with stakeholders for activation and consumption of trained predictive models.
- Provide insights to the team on impact of strategic initiatives, model metrics; and help them track progress towards goals.
- Document methods, guidelines, model governance, and best practices for repeatable data science projects to improve data driven culture.
- Provides guidance and share knowledge and best practices with other data scientists.
QUALIFICATIONS (KNOWLEDGE, SKILLS & ABILITES)
- In-depth knowledge of statistics, probability and machine learning with demonstrated professional experience
- Proficiency in one or more of the following: Natural Language Processing, pattern recognition, recommendation systems, targeting systems, ranking systems
- Proficiency or experience involving some of the following data types: fitness data, structured, non-structured, bio-mechanical, geographic, positional, time-series, multi-sensor, multi-data source, sparse and fine-grained data
- Proficiency or experience delivering predictive models in production environment
- Proficiency in providing written and oral interpretations of highly specialized terms and data
- Proficiency in presenting data to others with different levels of expertise
- ETL
- SQL
- Python or R
- Spark
- AWS
EDUCATION AND/OR EXPERIENCE:
- 3-5 years
- Bachelor or Masters Degree in Applied Statistics, Computer Science or related mathematical field
