Manager, Data Science

Cinch Careers Page- External•Boca Raton, FL

21h

About The Position

CINCH is looking to expand the use of Machine Learning in its business to drive outsized outcomes and contribute to the enablement of its AI strategy. To that end, we are looking for a hands-on working manager that also leads the work of our data science analyst(s) and guides the supporting data engineering functions. This manager will report to the Director, Data Science and Engineering in the Data & Analytics organization.

Requirements

5-7 years directly relevant experience
Hands high proficiency querying databases and using statistical computer languages: Python, R, SLQ.
Experience using web services: Redshift, S3, Spark, etc.
Experience creating and using advanced machine learning algorithms and statistical techniques: for example, regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc.
Experience deploying and monitoring statistical models at production scale in enterprises.
Experience analyzing data from 3rd party providers: Google Analytics, Site Catalyst, Coremetrics, Adwords, Crimson Hexagon, Facebook Insights, etc.
Experience visualizing/presenting data for stakeholders using: MicroStrategy or Tableau, D3, ggplot, etc.
Proven results, working directly with business leaders to design outcomes and paths for activation, deploying operational models in support of ai strategy, and
At least 2 years guiding the work of data science and data engineering analysts.

Responsibilities

Work with stakeholders throughout the organization and the Data & Analytics leaders to identify opportunities to optimize audience identification and segmentation, unknown/known target prospect marketing, customer lifecycle, customer satisfaction and operational efficiency.
Mine and analyze data from company and 3rd party databases to drive optimization and improvement of product development, marketing techniques and business strategies.
Assess the effectiveness and accuracy of new data sources and data gathering techniques.
Use predictive modeling to increase and optimize customer experiences, revenue generation, ad targeting and other business outcomes.
Develop company A/B testing frameworks to support test model quality.
Work to identify, specify and implement the platforms and operating processes to support deployment of models at scale into production, improve discovery and modeling efficiency, and to analyze model performance, drift and bias.
Coordinate with different functional teams to implement models and monitor outcomes.
Support the deployment of the company’s ai strategy through partnership with 3rd parties to provide modeled inputs that enable more targeting and next best action, and
Manage the work and delivery of the data science analyst(s).
Where applicable, build and maintain challenger statistical models to benchmark and manage the performance of 3rd party modeling providers