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# Data Scientist - Machine Learning & AI

- **Company:** ClearCompany
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Salary:** $160,000.0 - $190,000.0
- **Contract:** Permanent contract
- **Skills:** A/B Testing, Artificial Intelligence, Airflow, Amazon Web Services, Data Analysis, Artificial Neural Networks, Microsoft Azure, Software as a Service, Cloud Computing, Software Quality, Continuous Integration, Monitoring of Systems, Statistical Hypothesis Testing, Python (Programming Language), Machine Learning, Standard Sql, SQL Databases, Data Streaming, Google Cloud, Feature Engineering, Delivery Pipeline, Large Language Models, Snowflake, Grafana, Random Forest, Apache Spark, Deep Learning, Generative AI, Kubernetes, Information Technology, Xgboost, Machine Learning Operations
- **Published:** August 19, 2026
- **Apply:** http://teamvelocitymarketing.hrmdirect.com/employment/job-opening.php?req=3790676&req_loc=1435729&&

## About the Role

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., * 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., * 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

## Description

* 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.


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