Job Location: San Diego, CA, Indianapolis, IN or Louisville, KY (*No relocation available. Please do not apply if you do not already reside in one of these 3 locations*)
SmarterHQ was founded in 2010 by Angel Morales and Dean Abbott. Headquartered in Indianapolis, IN with offices in San Diego, CA. Louisville, KY and Austin, TX. SmarterHQ is a customer intelligence driven cross-channel marketing platform which enables retailers to leverage customer insights and experiences to create and execute the industry's most profitable cross channel marketing programs. SmarterHQ is able to reveal unique strategic and tactical marketing opportunities at all stages of the customer lifecycle by uniting and modeling in-store, mobile, desktop, in-app, and countless other sources of customer data to provide business critical insights such as future purchase probability, attrition risk, and shopper engagement. SmarterHQ's vendor-unifying, cross-channel marketing capability substantially bolsters the value of existing vendor relationships by enabling them to work together intelligently; sending incredibly relevant communication through most cost effective path possible.
Work Smarter
We’re a dynamic team comprised of people who view excellence as the expectation. We combine a start-up culture with an enterprise mindset, focusing on results, transparency and value delivered. We’re reputable enough to have gained the trust of major, global brands, but small enough to appreciate the importance of every individual team member. Best of all, we’re growing fast, which means you have the opportunity to develop personally and directly impact both your own path and the company’s.
Job Summary
SmarterHQ is seeking a brilliant and creative Data Scientist to join the team. To be a good fit, you must love data!
As a Data Scientist at SmarterHQ, you’ll play a major role in how we architect, collect, manipulate, and interpret critical data that is at the very core of our business. You’ll partner with our leaders to understand objectives, then work alongside our Analysts and Developers to implement analysis plans and communicate findings back to the business through documentation of the analyses to personnel internal to SHQ and reports to be used by clients.
Some days you will be deep in writing queries to build data. Other days you will be deep in writing, debugging, or assessing Python code or building predictive models. Some days you will be summarizing modeling results for internal solutions consultants to convey to clients. Be prepared to not only build data and predictive models, but understand and explain why they behave the way they do. Our data scientists live in a fast-paced world of data, bringing practical implementations of leading-edge analytics to our clients.
Ideal Candidate
We’re looking for someone who loves data, and not just how to build predictive models (the recipe) but what it means. Someone who dreams up creative solutions that break the mold, enjoys delivering value in solutions over and above what the theory alone would say to do. Someone who is independently motivated - can work alone without someone directing micro steps but enjoys discussing approaches and collaboration. And finally, someone who takes feedback not as criticism but as an opportunity to learn and grow as a professional.
Responsibilities
* Work comfortably with billion+ row tables
* Integrate multiple data sources and create derived variables and measures, in Amazon Redshift.
* Analyze and interpret data using advanced statistical methods using Python.
* Code Python for building predictive models
* Automate the building of tens of thousands of parametric and non-parametric models for each client.
* Summarize insights from predictive models for use in the user interface for reporting and customer segmentation
* Code SQL queries on Redshift to build data for reporting and modeling. Queries have to run at large scale
* Assess Models, provide proof and explanation for acceptance tests;
* Create Deployment code for queries and python to run automatically on historic data and for daily updates.
* Design algorithms for building data for modeling, building models.
* Interact with Development team for code reviews
* Collaborate within the data science team to discover new and creative ways to solve leading-edge problems facing retailers with predictive analytics.
* Collaborate with product team to identify data-driven solutions to ongoing needs of retailers