Data Scientist / Sr. Data Scientist
Data Scientist / Sr. Data Scientist – Los Angeles
Data Science and Analytics team at Tillster is looking for a highly motivated Data Scientist to work with rich consumer datasets. You will be building various machine learning and statistical models from Tillster’s own digital commerce & marketing platform data and third party data to optimize customer experience and profitability for global restaurant brands in the quick service and casual dining space.
You are details oriented and efficient, yet keep an eye on the bigger picture that drives the business/product goals. You are fundamentally a scientist who writes programs and scripts to analyzes any/all kind of data and who detects patterns and anomalies in data. You are comfortably familiar with statistical as well as machine learning concepts and can use them to dissect any/all data for making business decisions. You can quickly analyze a dataset to summarize it to a business executive for actionable insights.
You live and breathe concepts like box plots, Gini coefficient, normalization, probability distribution function, regression analysis, collaborative filtering, sampling, recommendation engines, optimizations, predictive analytics, retail analytics, marketing analytics, classification, clustering, A/B testing, etc. We value initiative and ability to work with minimal supervision, but we value equally the ability to follow direction and be part of the team. We thrive in a culture of respect and building technology together. We learn from each other.
- Identify and propose Data Science solutions for various marketing, engineering, business and product initiatives.
- Identify, propose and implement solutions for cross-selling, up-selling & suggestive selling and build recommender engines/models.
- Design and build predictive customer behavior models for targeting and personalization.
- Analyze, recommend and execute A/B and multivariate testing methodologies for mobile apps and responsive websites.
- Present analyses, actionable insights & recommendations to key stakeholders including senior executives & clients.
- 3+ years of experience in statistics, data mining and predictive modeling required.
- 3+ years of programming experience in R, Python, Java/Scala required.
- Proficiency with at least one visualization tool and/or library e.g. D3, Microsoft Excel, Tableau, etc.
- SQL & database experience.
- Experience in collecting data from/exposing data to various data sources and services (API, JSON, XML).
- Experience in implementing real-time machine learning and data mining algorithms in large scale environments a big plus.
- Experience with AWS cloud offerings especially S3 and Redshift a big plus.
- Experience with Google products especially Google Cloud Storage, Google Analytics and Google Big Query a big plus.
- Highly analytical and great problem solving skills.
- Great communication skills and ability to explain data and analysis to a variety of audience.
- Self motivation & enjoyment of a fast-paced environment.
- Bachelor’s degree in quantitative or related field (Graduate degree or higher preferred).
Tillster is the global leader in digital ordering and customer engagement solutions. For over a decade we’ve developed revolutionary self-service, ordering and payments solutions – for mobile, tablet, online, kiosk, call center, and more – creating personalized interactions based on consumer preferences, language, and currency. Our platform is compatible with 15+ unique POS systems, representing over 90% coverage in multi-unit restaurants. We offer one platform; one scalable, enterprise class solution – to create world-class digital engagement solutions.
Tillster is proudly an Equal Opportunity Employer
Local Candidates Strongly Preferred
Relocation Assistance Considered
No visa sponsorship
Principals only – no Agencies or calls please
Meet Some of Tillster's Employees
Senior Software Engineer, Front-end
Jason ensures that the quality and organization of the company’s code base is consistent. He also works to improve the usability and stability of Tillster’s web applications.
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