Staff Data Scientist

Company overview

Consumer Edge builds data and AI products that uncover consumer and business behavior across industries. Our Location team specializes in using geospatial and transaction data to generate market insights for enterprise clients.

Role summary

We are seeking an experienced and solutions-oriented Data Scientist to join our data team and tackle our most complex business challenges. This is a leadership role where you will not only build sophisticated models but also own the full data science lifecycle, from problem definition to stakeholder communication.

The ideal candidate is a technical expert who bridges the gap between raw data and actionable strategy. You will lead high-impact projects in areas like location analytics, time series forecasting, anomaly detection, and large-scale A/B testing. You must be a hybrid talent, combining deep statistical rigor and machine learning expertise with strong software engineering fundamentals. A critical part of this role is the ability to document design decisions rigorously and communicate findings effectively to both executive leadership and engineering teams.

Your main responsibilities

• Apply advanced geospatial techniques to solve challenging location analytics problems, deriving insights from spatial data.
• Design, build, validate, and deploy end-to-end machine learning models for key business problems, including anomaly detection and time series forecasting.
• Lead the design, execution, and statistical analysis of complex A/B tests and other experiments to drive and measure marketing activation.
• Perform deep-dive exploratory and statistical analyses using advanced SQL and Python to query, manipulate, and model large-scale, complex datasets.
• Champion software engineering best practices within the data science workflow, including code reviews, version control (Git), testing, containerization, and reproducibility.
• Clearly and proactively document technical design decisions, methodologies, and model limitations to ensure transparency and knowledge sharing.
• Translate complex analytical concepts and model outcomes into clear, actionable insights for non-technical audiences and senior leadership.
• Mentor junior data scientists and analysts, fostering a culture of technical excellence and continuous learning.

Required Experience

• 5+ years of hands-on experience in a data science or machine learning role.
• Expert-level proficiency in Python and its core data science libraries.
• Advanced proficiency in SQL, including window functions, common table expressions (CTEs), and query optimization.
• Deep understanding and practical application of machine learning algorithms (e.g., regression, classification, clustering, tree-based models) and statistical principles (e.g., hypothesis testing, experimental design).
• Proven experience leading projects in at least two of the following areas: location analytics, A/B testing, anomaly detection, or time series forecasting.
• Demonstrable experience writing clean, maintainable, and production-ready code, with a strong grasp of software engineering best practices.
• Exceptional written and verbal communication skills, with a proven ability to present complex technical information to non-technical stakeholders.
• Familiarity with cloud platforms (e.g., GCP, AWS,, Azure) and their associated data and ML services.

Desired Experience

• Experience with big data technologies (e.g., Apache Beam, Spark, Dask) and distributed computing environments.
• Experience with MLOps principles, including model deployment, CI/CD pipelines, and monitoring.
• Nice To Have
• Hands-on experience deploying LLMs and Generative AI to production systems.
• Specific experience with geospatial libraries (e.g., GeoPandas, PostGIS).
• Knowledge and practical application of Bayesian statistical methods (e.g., Bayesian inference, probabilistic programming using libraries like PyMC or Stan).
• Experience designing and implementing Multi-armed Bandit (MAB) algorithms for experimentation or personalization.

Tech stack & team context

The Location team works at the intersection of Data Science and Software Engineering, using Python, BigQuery, Vertex AI, and Dataflow. Collaboration is cross-functional with Basketview and AI Products teams, bridging data infrastructure and AI applications.

Benefits & perks

We are a remote-first company with a distributed environment and flexible working arrangements. We believe that distributed workers should be first-class citizens. We also have an office in New York if offices are your thing. 

Salary

The annual base salary for this role is between $275,000 – $325,000 based on experience, with the opportunity for a performance-based bonus, company equity, 401(k) matching, paid parental leave, flexible and generous time off, work-from-home flexibility, and subsidized health benefits.