Data Scientist

Stealth Startup; San Francisco (CA); On-site; USD 140,000 - 190,000; Full time

Job summary

Ever is seeking a Data Scientist to partner with Product, Engineering, Operations, and business teams. You will analyze complex datasets, develop predictive models, and build data-driven solutions for the automotive retail platform.

The role suits a proactive analyst who thrives in a fast-moving startup, taking problems from exploration to business impact.

Qualifications

• 3+ years in Data Science, ML, or related field.
• Strong Python and SQL proficiency.
• Experience with ML libraries (scikit-learn, pandas, NumPy).
• Solid understanding of statistics, probability, regression, classification, and experiments.
• Experience building/predictive models and data pipelines.
• Ability to communicate findings to non-technical stakeholders.
• Experience cross-functionally with Product/Engineering/Operations.

Responsibilities

• Analyze customer, vehicle, marketplace, sales, pricing, and operational data to identify trends.
• Develop and deploy statistical and ML models for business use cases.
• Build predictive models for customer behavior, pricing, inventory, and demand forecasting.
• Perform exploratory data analysis and define KPIs.
• Design and analyze A/B tests and experiments.
• Create forecasts, classifications, regressions, clustering, and recommendations.
• Collaborate with engineers to productionize models and data products.
• Translate business problems into measurable analytical solutions.
• Create dashboards, reports, and visualizations to communicate findings.
• Monitor model performance and improve accuracy and reliability.
• Work with SQL and Python on large datasets.
• Contribute to Ever’s broader AI and data strategy.

Skills

Python

SQL

Statistics

Data analysis

Experiment design

Communication

Tools

scikit-learn

pandas

NumPy

PyTorch

TensorFlow

Snowflake

BigQuery

AWS

Spark

Job description

As a Data Scientist, you will work closely with Product, Engineering, Operations, and business teams to analyze complex datasets, develop predictive models, identify trends, and build data-driven solutions that improve Ever’s automotive retail platform.

This role is ideal for someone who enjoys working in a fast-moving startup environment and can take a problem from data exploration modeling experimentation business impact.

What You’ll Do

• Analyze customer, vehicle, marketplace, sales, pricing, and operational data to identify trends and opportunities.
• Develop and deploy statistical and machine-learning models for business and product use cases.
• Build predictive models for areas such as customer behavior, vehicle pricing, inventory, demand forecasting, lead conversion, and sales performance.
• Perform exploratory data analysis and develop meaningful KPIs and metrics.
• Design and analyze A/B tests and other experiments.
• Build forecasting, classification, regression, clustering, and recommendation models where appropriate.
• Collaborate with engineers to productionize machine-learning models and data products.
• Work with Product and Operations teams to translate business problems into measurable analytical solutions.
• Create dashboards, reports, and data visualizations that communicate findings clearly.
• Monitor model performance and continuously improve model accuracy and reliability.
• Work with large and complex datasets using SQL and Python.
• Contribute to Ever’s broader AI and data strategy.

Required Qualifications

• 3+ years of experience in Data Science, Machine Learning, Applied Statistics, or a related field.
• Strong proficiency in Python.
• Strong proficiency in SQL.
• Experience with machine-learning libraries such as scikit-learn, pandas, NumPy, or equivalent.
• Strong understanding of statistics, probability, regression, classification, and experimental design.
• Experience building and evaluating predictive models.
• Experience working with large datasets and data pipelines.
• Strong analytical and problem-solving skills.
• Ability to communicate technical findings clearly to non-technical stakeholders.
• Experience working cross-functionally with Product, Engineering, or Operations teams.

Preferred Qualifications

• Experience with PyTorch or TensorFlow.
• Experience with forecasting, recommendation systems, optimization, NLP, or time-series modeling.
• Experience with cloud data platforms such as Snowflake, BigQuery, or AWS.
• Experience with Spark or distributed data processing.
• Experience working with production ML systems or MLOps.
• Experience in automotive, mobility, e-commerce, marketplace, fintech, or other high-volume transactional environments.
• Startup experience with high ownership and rapidly changing priorities.

What We’re Looking For

• Strong ownership and ability to work independently.
• A practical, business-oriented approach to Data Science.
• Curiosity about AI, machine learning, and emerging technologies.
• Ability to move quickly from analysis to implementation.
• Strong communication and collaboration skills.
• Comfort working in an ambiguous, fast-paced startup environment.