GAP - Senior Manager - Platform Analytics

We are looking for a Sr. Manager who will be leading a team of data scientists focused on building data science products using advanced statistical models and machine learning algorithms and will be pivotal in leading the delivery of industrial grade predictive analytics built for scale, repeatability and adaptability.

If you are passionate about providing customer centric solutions and enjoy working with best in analytics products, we should talk!

Key Responsibilities :

Implementing Data Science Solutions : 

- Builds predictive models using algorithms such as Logistic Regression, Bagging, Boosting, SVMs, Deep Learning frameworks etc. Provide actionable recommendations based on insights, and report on these insights to business and technical partners

People Leadership : 

- Leads the team by creating a culture of trust, honesty and accountability by fostering partnerships with teams within the Customer Data and Analytics organization as well as external business functions to understand requirements, propose data science solutions and implement strategies that will drive personalized experiences for our customers

Model Deployment and Production : 

- Builds extensible, repeatable and scalable models that will be deployed in partnership with Gap Tech and can be embedded in our Customer Data Platform to enable near real-time decisions. Operational excellence in this responsibility is critical.

Learning and Development : 

- Evangelizes adoption of technology, best modeling and coding practices within and across the Customer Data and Analytics functions. Cultivate a culture of learning and continued development through mutual sharing of knowledge with other teams

Capabilities & Requirements :

- 7-8 years of experience in core data science and customer analytics functions

- Broad experience analyzing massive datasets in Hadoop environment as well relational databases

- Experience designing and validating models using logistic regression, decision trees, non-linear regressions, boosted trees, support vector machines, deep learning frameworks

- Demonstrable experience in building predictive models and algorithms that directly power data science products

- Expert knowledge of statistical software such as R or Python. Knowledge in SAS is good to have but not required

- Experience in Hive HQL, SQL, Spark, Pig

- MS/PhD, preferably in statistics, computer science, mathematics, economics or a technology focused degree