Lead Data Scientist, Product (Remote)

ezCater is the most trusted provider of corporate food solutions and is purpose-built for business. ezCater's corporate food platform and flexible, scalable food solutions allow organizations to centralize and track their food spend, and fulfill everything from daily employee meals to client meetings and company all-hands. ezCater backs this up with business-grade, best-in-class, customer service and an unmatched nationwide footprint. We're backed by top investors including Insight, Iconiq, Lightspeed, GIC, SoftBank, and Quadrille.

Data and analytics are critical to our future growth at ezCater. Equally as important, is how we transform that data into value-add product business decisions, leveraging our product data assets. As a Lead Data Scientist on the Product Analytics Team, you will bring an unparalleled depth of insights, and unlock numerous opportunities for the business. You will be responsible for leading the advanced modeling and analytic efforts for critical product questions requiring data science expertise, including but not limited to developing models to: assess and predict caterer potential performance and identify improvement opportunities; assess and predict order delivery performance to proactively address order reliability risks; better understand customer segments  and which product features are most relevant to optimizing the customer experience and improving customer LTV.  Your work on these projects will enable partners and stakeholders from across the business to drive value and best serve our customer’s needs where data science methods are necessary to answer the business question. The ideal candidate is a strong critical thinker, independent worker who can deliver on open-ended questions while working closely with collaborative partners.

What You'll Do:

• Data Analysis and Interpretation: Use advanced statistical techniques such as Bayesian and causal inference to analyze large datasets, extract meaningful insights, and provide actionable recommendations for product improvements.
• A/B Testing: Design, implement, and execute A/B tests to evaluate the impact of different product changes and features on user engagement, retention, and conversion rates.
• Predictive Modeling: Develop predictive models to forecast user behavior, identify trends, and anticipate customer needs, contributing to data-driven decision-making in product development.
• Experimentation and Analytic Innovation: Explore new data sources, techniques, and technologies to enhance the data science capabilities and contribute to innovation within the product development process.
• Machine Learning Model Integration: Partner with our ML team to integrate data science models and algorithms into the product in the most valuable and effective manner, including providing personalized experiences, recommendations, and features for users.
• Continuous Learning: Stay up-to-date with the latest developments in data science, machine learning, and relevant industry trends, applying these insights to your work.
• As an individual contributor, be the advisor and subject matter expert for structural design of data, analysis, experiments, and modeling for your domain; advance innovation and improvements to the analytics techniques, approaches, and processes used across the company.

What You Have: 

• 5-7 years experience in data science, statistics, computer science, or a related field, performing statistical modeling and quantitative and technical analysis, ideally with experience in marketplace or e-commerce environments.
• Experience proactively identifying areas where analytical efforts can add strong business value and setting the analytics roadmap.
• Experience in deploying and maintaining data science & machine learning algorithms that are widely used and adopted.
• Demonstrated proficiency in explaining complex analysis to stakeholders at all levels of the organization and translating conclusions into straightforward, actionable business recommendations and strategic direction. Includes creating clear and compelling visualizations to communicate complex data.
• Demonstrated ability collaborating with cross-functional teams, including product managers, engineers, analysts, and designers, to define and address key business challenges using data-driven approaches.
• Self-directed and demonstrated ability to define, prioritize, and direct analytics initiatives
• Proficiency in SQL, Python, and Python libraries such as Pandas, Numpy, and scikit-learn.
• Knowledge of data science / ML modeling approaches (e.g. time series forecasting, logistic regression, and gradient-boosted decision trees).
• Experience partnering with business teams on nimble and rapid model development.