Key Responsibilities:
Manage and mentor a team of 46 data scientists and lead the hiring of new scientists for continuous team growth;
Oversee and own data science projects throughout the project lifecycle including scoping development validation implementation and ongoing maintenance;
Participate in the development of proposals and scope documents and present to clients;
Interface with business stakeholders (internal or external) to identify business challenges that require datadriven approach;
Design data science project plan and build effort estimation to maximize business impact and ensure that projects are completed on time within budget and to business stakeholders satisfaction;
Teach lead and counsel colleagues on new ML techniques or solutions;
Build client facing presentations to review analytic results and ability to convey technical concepts around analytic solutions to nontechnical audiences in compelling story;
Design project milestone deliverables and review midproject deliverables for adherence to highest standards;
Build new predictive models segmentations and algorithms; as well as analyze preexisting analytic solutions provide suggestions on how to evolve and improve their efficiency and effectiveness;
Ensure data and code integrity by conducting documentation and code reviews;
Drive ontime delivery and identify and resolve project risks with support of Directors;
Align managers goal to ensure business and directors goals are achieved for the year;
Qualifications and Technical Skills:
MS/PhD. Data Science Statistics Economics Computer Science Mathematics or related applied quantitative field;
6 years developing predictive models and creating and using machine learning algorithms;
Proficient level of understanding in machine learning and deep learning methods including familiarity with techniques in clustering classification regression optimization recommendation natural language processing;
Excellent programming skills in SQL and Python;
Programming skills in Spark Java Scala are strongly desired;
Strength in clarifying and formalizing complex problems;
Proven track record of business integration and productization of Data Science solutions;
Experience ingesting and manipulating large volumes of data (both tall and wide format);
Experience with at least one of the following: Azure Databricks AWS;
Experience using deep learning libraries (PyTorch Tensor Flow Keras) is strongly desired;
Experience in developing DS solutions for digital marketing is preferred;