Data Scientist (L5), CoBRA
DESCRIPTION
IN Consumer BI Reporting and Analytics (COBRA) team is looking for a highly driven, customer-obsessed Data Scientist who will be responsible for scaling Insights & Science charter across Category & Seller orgs and enable effective business decision making across IN Stores. You’ll analyze large amounts of data, discover and solve real world problems, build science-driven solutions around key projects and, most of all, be an integral part of creating a better customer and seller experience.
We are looking for customer obsessed, data driven entrepreneurs to join our growing team and solve some of the hardest problems for our customers. If you want operate at start up speed, solve some of the hardest problems and build a service which customers love, this role might just be the place for you. The Data Scientist is responsible for unlocking business value across IN Stores through advanced analytics (ML, Science/Statistics). The Data Scientist's responsibilities include, but are not limited to the following points:
-Collaborate with business stakeholders and product/program managers to innovate on behalf of customers leveraging data science methodologies, and partner with Data engineers and BiE's to design, develop, and scale machine learning models
-Use computational methods to identify relationships between business data and outcomes, define outliers and anomalies, and justify those outcomes to business customers
-Develop code to analyze data (SQL, PySpark, Scala, etc.) and build statistical and machine learning models and algorithms
-Work with distributed machine learning and statistical algorithms to harness enormous volumes of data at scale to serve our customers
-End-to-end ownership of operational and technical aspects of the insights you are building for the business, and play a critical role in enabling science based decision making for business
- Have excellent business and communication skills to be able to work with business owners to develop and define key business questions and build mechanisms that answer those questions
BASIC QUALIFICATIONS
- 2+ years of data scientist experience
- 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
- 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
- Experience applying theoretical models in an applied environment
PREFERRED QUALIFICATIONS
- Experience in Python, Perl, or another scripting language
- Experience in a ML or data scientist role with a large technology company