This contract position is with one of our Direct Clients. Please submit resumes to Simone-spereira(at)divihn(dot)com or call Simoneta - 630 847 0953 with any questions.
Job Title: Sr Digital Product Data Scientist
Job Type: Direct Hire
Location: Austin (first choice); San Francisco/Bay Area then Baltimore (3rd choice)
A Senior Digital Product Data Scientist at Client 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. The 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 Client's customers, and MapMyRun's user base.
ESSENTIAL DUTIES and 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 the 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 the data-driven culture at the company.
Provides guidance and share knowledge and best practices with other data scientists.
QUALIFICATIONS (KNOWLEDGE, SKILLS and 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 a 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
- Python or R
EDUCATION AND/OR EXPERIENCE:
Bachelor or Master's Degree in Applied Statistics, Computer Science or related mathematical field OTHER REQUIREMENTS:
BENEFITS AND PERKS (General Corporate Perks):
Paid Client Give Back Volunteer Days: Work alongside your team to support initiatives in your local community.
Client Merchandise and Connected Fitness app Discounts.
Competitive 401(k) plan matching.
Maternity and Parental Leave for eligible and FMLA-eligible teammates
Health and fitness benefits, discounts, and resources- We offer teammates across the country programs to promote physical activity and overall well-being.
About us: DivIHN, the 'IT Asset Performance Services' organization, provides Professional Consulting, Custom Projects, and Professional Resource Augmentation services to clients in the Mid-West and beyond. The strategic characteristics of the organization are Standardization, Specialization, and Collaboration.
DivIHN is an equal opportunity employer. DivIHN does not and shall not discriminate against any employee or qualified applicant on the basis of race, color, religion (creed), gender, gender expression, age, national origin (ancestry), disability, marital status, sexual orientation, or military status.