Senior data scientist � machine learning & ai

Senior Data Scientist – Machine Learning & AI

Remote | Full-Time | $160,000–$190,000

Team Velocity is seeking a Senior Data Scientist to develop and deploy machine learning, predictive analytics, and AI solutions that improve customer engagement, marketing performance, operational efficiency, and business intelligence. This is a hands-on role for an experienced data scientist who can take models from data exploration and development through production deployment, monitoring, and optimization. You will partner with Product, Data Engineering, Software Engineering, Analytics, and business leadership to deliver measurable business impact. This is a full-time remote position. Candidates must reside in the Continental U.S. and be able to support an 8:30 AM–5:30 PM ET business hours. Eastern and Central Time Zones highly preferred.

KEY RESPONSIBILITIES

• Design, build, evaluate, and deploy production machine learning models.
• Develop predictive models for churn, propensity, lead scoring, customer lifetime value, recommendations, forecasting, personalization, and marketing attribution.
• Perform statistical analysis, hypothesis testing, A/B testing, causal inference, and time-series analysis.
• Build feature engineering, model training, and inference pipelines.
• Deploy and monitor ML models, including model performance, drift detection, and retraining.
• Apply Generative AI, LLMs, RAG, and vector databases to business and customer applications.
• Partner with Product, Engineering, Analytics, and leadership to translate business problems into scalable data science solutions.
• Mentor junior data scientists and establish best practices for model development, documentation, and code quality.

REQUIREMENTS

Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or related field; Master's or PhD preferred.

5+ years | Python + SQL | production ML | predictive modeling | model deployment | MLOps | cloud | measurable business impact

Proven ability to deliver measurable business impact through data science and machine learning. Strong communication, analytical, and business problem-solving skills. Expert Python and SQL skills.

TECHNICAL EXPERIENCE

• Machine Learning: XGBoost, LightGBM, Random Forest, Neural Networks, Deep Learning
• Statistics: Regression, Bayesian methods, hypothesis testing, experimental design, causal inference, time series
• Data & Cloud: Snowflake, dbt, Spark, Airflow, GCP preferred; AWS or Azure considered
• MLOps: MLflow, Kubeflow, Vertex AI, feature stores, CI/CD, model monitoring
• AI/LLMs: OpenAI, Gemini, Claude, LangChain, LangGraph, RAG, embeddings, vector databases

Experience with data quality and observability tools such as Great Expectations or Monte Carlo is a plus. *You do not need experience with every technology listed above. Strong production machine learning experience is the priority.

Preferred Experience

• Large-scale customer or behavioral data
• Marketing analytics, personalization, or customer intelligence
• SaaS, automotive, retail, advertising, or marketing technology
• Real-time inference or streaming data
• Production Generative AI applications

COMPENSATION & BENEFITS

The expected salary range is $160,000–$190,000 annually, based on experience, skills, and qualifications. Benefits include medical, dental, vision, 401(k) matching, unlimited paid leave, wellness programs, and more.

NEXT STEPS

If you meet the requirements, and are interested in applying for this role, please complete the online employment application and be sure to upload a current resume and current contact information.

About Team Velocity

Team Velocity is a full-service marketing and technology company serving automotive manufacturers and dealerships nationwide. Our proprietary Apollo™ technology platform uses data, predictive analytics, and AI to predict consumer behavior, personalize marketing, and help dealerships increase sales and service revenue. Join us in applying data science, machine learning, and AI to real-world business problems at scale.