Principal Data Scientist

Bolt is on a mission to democratize commerce. Since our founding, we’ve relentlessly focused on creating a world class buying experience that’s available for all online businesses – not just the giants of retail. Through CheckoutOS and our growing network of tens of millions of shoppers ready for one-click-checkout at the point of inspiration, Bolt is leveling the playing field for retailers and making shopping easy, trusted, and secure for consumers. 

The fact that we're revolutionizing ecommerce is only half of the equation – we’re also transforming the way we work. At Bolt, we’re committed to working Consciously, and believe in balancing execution with humanity. Our team is driven by the great technical challenges in our path, and by the thrill of creating a new standard for work. Come join us on the adventure today!

The Data Platform team works closely with all teams and cross-functional partners (including product, engineering, and data analysts) to build a foundational data stack powering business analytics.

We are looking for someone to play a mission-critical role in designing and building the machine models for Recommendations, Personalization, Risk, and Fraud that powers Bolt. This should be someone with experience, creativity, and passion for producing world-class technology. Companies and consumers alike will rely heavily on what you build, and you’ll have a ton of trust and responsibility. If challenges excite you, and you’re ready for a large one, let us know.

Responsibilities

• Build production ready machine learning models; your models will be the engine that powers all online commerce through Bolt
• Conduct data analysis to determine which policies we adopt and help inform strategic growth
• Build machine learning infrastructure, data pipelines and production ready services to serve live traffic
• Work with other teams at Bolt to engineer new features for models or new product features that help improve Bolt business
• Be the go to technical individual contributing leader for all Data related questions, tasks, and projects at Bolt

Requirements

• Degree in Computer Science, Computer Engineering, or related field
• 7+ years of experience building machine learning models for personalization, recommendation, or similar applications.
• Thorough understanding of machine learning fundamentals and methodologies
• Experience building and deploying machine learning models in an applied setting
• Strong understanding of how to build scalable ML systems supporting online and offline applications
• Experience working with machine learning libraries and frameworks such as scikit-learn, TensorFlow, PyTorch, Spark ML
• Familiarity with best practices of lifecycle management for ML models in industry
• Mastery of a programming language such as Python, Java, Scala

Preferred

• PhD in computer science or related field
• Experience with big data technologies such as BigQuery, Spark, Dataflow, Apache Beam, Pubsub, Cloud Functions, EMR, S3, Glue, Kinesis Firehose, Lambda, etc.
• Industry experience in building large-scale recommendation systems in a consumer-based setting.

Check out our Engineering Blog! 

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Benefits:

• Comprehensive health coverage: Medical, dental and vision
• Remote-first workplace
• 4 day work weeks
• Time away: Flexible PTO, paid holidays + floating holidays, your birthday off!
• Paid parental leave
• Competitive Pay
• Retirement plans
• Virtual and in-person team & company events

In addition to our core values, Bolt is proud to be an equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity and expression, genetic information, pregnancy and related conditions, veteran status or any other reason prohibited by law. On our mission to democratize commerce, the Bolt platform levels the playing field for everyone. As a company, we are committed to designing products, building a culture, and supporting a team that reflects the diverse population we serve (that is, everyone).