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Lead Data Scientist

Chelsoft Solutions Co.Bethesda, MD🇺🇸United StatesPosted 2 Sept 2026

Quick Overview

Seniority
Mid Senior
Work mode
On Site
Location
Bethesda, MD, United States
Posted
19 hours ago
DockerSQLMLOpsMachine LearningKubernetesPython

Job Description

Lead Data Scientist

Location: Bethesda, MD or Boca Raton, FL – 5 Days Onsite
Duration: 6-Month Contract-to-Hire
Work Authorization: Open to Sponsorship
Experience: 5–8 Years

We are seeking an experienced Lead Data Scientist to design, develop, deploy, and monitor production-grade Machine Learning and AI solutions. The ideal candidate will have strong hands-on expertise across the complete ML lifecycle and experience translating complex business problems into scalable technical solutions.

Key Responsibilities

  • Design and develop advanced Machine Learning and AI models.

  • Perform feature engineering, algorithm selection, model training, hyperparameter tuning, and validation.

  • Build scalable ML training and evaluation pipelines.

  • Deploy ML models into production using CI/CD, Docker, Kubernetes, and cloud technologies.

  • Implement model monitoring, data/model drift detection, alerting, and automated retraining.

  • Conduct model performance, fairness, bias, and error analysis.

  • Translate model performance into measurable business outcomes.

  • Mentor junior Data Scientists and provide technical leadership.

  • Communicate technical solutions, results, and trade-offs to business stakeholders.

Required Skills

  • 5–8 years of experience in Data Science, Machine Learning, Predictive Analytics, or related fields.

  • Expert-level Python and SQL.

  • Strong experience with Machine Learning/AI model development and production deployment.

  • Strong knowledge of feature engineering, model optimization, cross-validation, and hyperparameter tuning.

  • Experience with MLOps, CI/CD, Docker, Kubernetes, and cloud environments.

  • Experience with model monitoring, drift detection, retraining, and ML governance.

  • Strong communication, mentoring, and technical leadership skills.

Education: Bachelor’s degree in Data Science, Computer Science, Mathematics, Statistics, Economics, or related field. Master’s degree preferred.

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