Data Scientist

ClearCompany
United States
about 1 month ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Working hours
Regular working hours

Tech stack

Artificial Intelligence Airflow Amazon Web Services Data Analysis Artificial Neural Networks Microsoft Azure Software as a Service Cloud Computing Code Review Continuous Integration Customer Data Management Extract Transform Load (ETL)
+15 more
Statistical Hypothesis Testing Python (Programming Language) Machine Learning Standard Sql Google Cloud Feature Engineering Large Language Models Snowflake Apache Spark Deep Learning Pandas Kubernetes Information Technology Xgboost Machine Learning Operations

Job description

  • Design, build, train, evaluate, and deploy machine learning models.
  • Develop predictive models including churn, propensity, lead scoring, customer lifetime value, recommendation engines, forecasting, and marketing attribution.
  • Perform statistical analysis, hypothesis testing, causal inference, and A/B test analysis.
  • Build feature engineering and model training pipelines.
  • Deploy and monitor production ML models, including model drift detection and retraining.
  • Collaborate with Product, Engineering, Analytics, and executive leadership.
  • Mentor junior data scientists and establish best practices.

Requirements

  • Bachelor’s degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or related field, Master’s or PhD preferred
  • 5+ years of experience building and deploying production ML systems, with a track record of measurable business impact
  • Strong communication and business problem-solving skills

Technical Skills

  • Expert Python and SQL
  • Machine Learning: XGBoost, LightGBM, Random Forests, Neural Networks, Deep Learning
  • Statistics: Regression, Bayesian methods, hypothesis testing, experimental design, time series, causal inference
  • Snowflake, Matillion, dbt, Pandas, Spark, Airflow
  • Cloud: Google Cloud (preferred), AWS, or Azure
  • MLOps: MLflow, Kubeflow, Vertex AI Pipelines, Feature Stores, CI/CD
  • Data quality and observability: Great Expectations, Monte Carlo, or similar frameworks
  • LLMs and AI: OpenAI, Gemini, Claude, LangChain, LangGraph, Semantic Kernel, RAG, vector databases

Preferred Experience

  • Large-scale customer data platforms
  • Marketing analytics and personalization
  • Automotive or SaaS industry experience
  • Real-time inference and streaming platforms

Success Metrics

  • Deliver production-ready ML models with measurable business impact
  • Improve prediction accuracy and operational efficiency
  • Implement model monitoring and retraining
  • Mentor team members and establish Data Science best practices
  • Contribute to team capability growth through documentation, code review standards, and mentorship outcomes that raise the overall quality of the Data Science function

Benefits & conditions

Compensation commensurate on experience. Participation in company benefit offerings include medical, dental, vision, unlimited paid leave, 401(k) matching, wellness, and more.

About the company

About Team Velocity Team Velocity is a full-service marketing agency serving the automotive industry, providing integrated marketing solutions to OEMs and dealerships nationwide. We leverage our proprietary Apollo® technology platform to predict consumer behavior, personalize marketing campaigns, and help dealerships drive more sales and service revenue.

Our team members are driven, creative, and collaborative, enjoying a unique culture where innovation and client success are paramount.

Join us in revolutionizing automotive marketing and technology through powerful, data-driven insights, continuous improvement, and an unwavering commitment to reliability.

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on teamvelocitymarketing.com

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