Lead Data Scientist

Overview

Our growing Analytics team is looking for our first Data Scientist to join our ranks, who can take on a “full-stack” role in building our data science infrastructure and partnering with other teams to build effective and impactful data science tools, such as our core receipt-to-transaction matching infrastructure and algorithms. You’ll report to the Director of Product Operations & Analytics, and partner with product, analytics, data ops, and data platform engineering teams to understand key data science needs, develop KPIs, build roadmaps, and create models and deployment infrastructure. We are searching for someone who is passionate about our mission, has the vision and desire to build from scratch, and can shape and manage a data science roadmap in a quickly growing product organization. The ideal candidate is excited to adapt to the evolving priorities of a growing startup – which may mean writing production-level code for our receipt-to-transaction matching infrastructure one day, while collaborating with data analysts or analytics engineers on key business analytics priorities the next.

What you’ll do

• Build and maintain end-to-end modeling pipelines and infrastructure, in partnership with analytics and engineering teams
• Conduct model experiments and feature engineering to transform raw receipt, merchant, and transaction data into useful, high quality data for modeling
• Deliver actionable guidance and recommendations to internal product and business stakeholders to help understand nuances of the models built and tactics for improving
• Become the subject matter expert on Banyan’s data matching process, working closely with internal business partners to help customers better understand their data
• Collaborate with our data platform team to identify valuable third-party data sources to augment our models

What you bring

• 4+ years of experience in data science, preferably in a tech company or startup
• Proficient in Python, and the ability to design, develop, and test customized pipeline and predictive modeling tools
• Experience developing and owning production-level models using real-world data
• Proficient in SQL, relational databases, and the modern data stack
• Experience with applied statistics and predictive modeling, with a structured framework for selecting the right modeling approach, tuning, evaluating model performance, and debugging modeling issues
• Good communication skills (written and verbal)
• Attention to detail and desire for end-to-end ownership of deliverables
• Self-motivated, proactive, and fairly autonomous; comfortable working in a fast-paced environment
• Collaborative with a positive attitude, interest in learning, and strong sense of empathy

Bonus points for

• Experience or familiarity with entity resolution / record matching, or natural language processing
• Experience with ETL pipelines, batch/real-time data processing, and dbt or similar tooling
• Familiarity with retail media, CPG, or financial transaction data We recognize that many great applicants will come with differing levels of experience and backgrounds (or may not have worked with the specific tools in our stack), so if you are interested in the role and passionate about our company vision and mission, but feel discouraged because you don’t match all the items, please apply anyway – there’s a good chance you also have important skills we haven’t stated.

Benefits

• Competitive salary and equity
• Medical, dental, and vision insurance plans
• Flexible vacation policy
• Paid parental leave
• Work-from-home remotely, w/ occasional travel (job-dependent)
• Option to work semi-regularly in office if located near Chicago, IL or Holmdel, NJ offices
• Learning and development initiatives & assistance

BANYAN is an equal opportunity employer and committed to providing employees with a work environment free of discrimination and harassment. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.