Data Analyst

South San Francisco
Product Development – Data Science Team /
Full-time /
The Data Science team uses data from Tally and computer vision models to ensure our customers derive the highest value from Simbe’s services. This includes developing new ways for customers to interact with Tally data, monitoring the performance of the computer vision models and robot hardware, and investigating service issues. You will play a key role in enabling Simbe to scale and service new environments using a data-driven approach.

We are looking for a data analyst who can dive deep into our data via SQL, dashboards, and manual review in order to create actionable plans to improve service.  This will include:
- Monitoring and investigating incoming customer support tickets to ensure​ customer feedback is clearly captured, investigated, and conveyed internally to enable ongoing improvement of ​Tally products and services.
-Providing day-to-day support for our customers, including both incident management and providing recommendations to ensure customers can get the most out of our platform
-Effectively triaging and managing escalations to engineering teams for issues that cannot be resolved
-Support our sales and customer success team members via custom SQL queries and by effectively communicating data concepts.   
-Reviewing customer-facing reports to identify the underlying reasons for errors. 
-Documenting database structures, metrics definitions, and other best practices to better enable our support team​.

-Strong attention to detail and being a self-directed problem solver
-Ability to adapt and pivot in a fast-paced environment
-A desire and aptitude to learn and understand new technologies
-Ability to dissect high-level trends to uncover individual occurrences, enabling detailed insights and targeted actions.   
-Hands-on experience with SQL
-Hands-on experience with dashboarding
-Knowledge of APIs and Python 
-Familiarity with Git is a plus
-Retail Domain knowledge is a plus
$75,000 - $125,000 a year
Salary range (above) is dependent on experience and location.