About Us

Simon Data was founded in 2015 by a team of successful serial entrepreneurs. We're a data-first marketing platform startup, and we approach our work seriously; we tackle problems in a scrappy and disruptive fashion, yet we build for scale to support our clients at big data volume.

Simon Data is a data-first customer experience orchestration platform, designed to disrupt the marketing technology and marketing cloud category. Simon’s platform empowers businesses to use enterprise-scale big data and machine learning to power customer communications in any channel. Simon’s unique approach allows brands to develop incredible personalization capabilities without needing to build and maintain massive bespoke data infrastructure.

Our culture is rooted in organizational transparency, empowering individuals, and an attitude of getting things done. If you want to be a valuable contributor on a team that champions these core values we would love to hear from you.

What You’ll Do

• Build ML products that use Simon’s outstanding data access to drive real business value
• Build high-quality statistical models by executing the entire model-building process, including data cleaning, feature extraction, model selection, and predictive validation
• Contribute to the tooling and interfaces used to support the data science process at Simon
• Represent Simon DS in conversations with partners at our client companies
• Advance Simon as a thought leader in data science, by writing blog posts and papers, and presenting at industry conferences
• Guide internal product and technology strategy by representing data science perspectives and requirements in conversations with your peers

Qualifications

• Ph.D. in Statistics/Machine Learning, or equivalent
• Excellent communication of statistical concepts to expert & non-expert audiences
• Broad and up-to-date knowledge of machine learning models (and their performance characteristics) for classification and regression tasks
• Specific experience designing and building machine-learning models
• Proficiency in at least one statistical coding environment (numpy/pandas, R, etc.)
• Comfort coding in at least one non-statistical language (e.g. Python or Java, not R or Matlab)
• Proficiency in SQL
• Production-level software engineering experience is a plus
• Expertise in causal inference, experiment design, reinforcement learning, and related fields is a plus

Diversity

We’re proud to be an equal opportunity employer open to all qualified applicants regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or expression, Veteran status, or any other legally protected status.