Senior Lead Consultant (Data and Machine Learning)

Apex Systems-posted 29 days ago
Full-time • Mid Level
Glen Allen, VA
501-1,000 employees
Administrative and Support Services
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Apex Systems is seeking a Senior Lead Data and Machine Learning Consultant to guide clients in developing scalable data and ML solutions built on modern cloud and big data platforms. The ideal candidate will combine strong technical expertise with consultative delivery skills, enabling enterprise clients to modernize their data foundations, implement explainable ML systems, and accelerate business outcomes through data-driven innovation. The Senior Lead Consultant will serve as the technical lead on engagements-defining architecture, leading implementation teams, development of POCs, and advising client stakeholders on data strategy, ML development, and production readiness.

  • Serve as the technical lead for data and ML initiatives, ensuring high-quality execution and alignment with best practices.
  • Lead the end-to-end design and implementation of scalable data and ML solutions using Apache Spark as the core processing engine.
  • Define architecture for data ingestion, transformation, feature engineering, and model deployment pipelines.
  • Build proofs of concept (POCs) to demonstrate model feasibility, performance, and value before full-scale implementation.
  • Evaluate tradeoffs between supervised and unsupervised learning methods, tree-based models, and deep learning architectures.
  • Partner with client data teams to assess data quality, structure, and availability.
  • Guide feature extraction, data profiling, and exploratory data analysis to inform model strategies.
  • Develop explainable and interpretable ML models to support business trust and adoption.
  • Build and validate ML models using Spark MLlib and Python-based frameworks (e.g., scikit-learn, PyTorch, TensorFlow, MLflow).
  • Apply MLOps best practices for model versioning, experimentation tracking, and reproducibility.
  • Conduct comparative analysis of models and techniques to determine the optimal production approach.
  • Optimize data and ML pipelines for performance, scalability, and cost efficiency.
  • Ensure solutions meet enterprise standards for governance, monitoring, and operational stability.
  • Serve as a trusted advisor to client leadership on data architecture, ML strategy, and technology roadmap.
  • Communicate technical concepts clearly to both technical and non-technical stakeholders.
  • Mentor junior engineers and consultants, fostering knowledge sharing and technical excellence.
  • Stay current with emerging technologies and trends in big data, ML, and AI, proactively identifying opportunities for innovation.
  • 8+ years of experience in data engineering, data science, or ML solution architecture roles.
  • Strong hands-on experience with Apache Spark (required).
  • Experience designing and deploying scalable data and ML pipelines in cloud environments (Azure, AWS, or GCP).
  • Proficiency with PySpark, SQL, and Python-based ML frameworks.
  • Proven ability to build and evaluate ML models (supervised/unsupervised, traditional vs. deep learning).
  • Excellent communication and client engagement skills with the ability to lead discussions with business and technical stakeholders.
  • Bachelor's degree in Computer Science, Information Systems, Engineering, or a related discipline (advanced degree preferred).
  • Experience delivering solutions on Databricks (Delta Lake, MLflow, Unity Catalog) preferred.
  • Understanding of explainable AI (XAI) and model interpretability techniques preferred.
  • Experience implementing MLOps practices such as CI/CD, model monitoring, and retrainingpreferred.
  • Experience with sensor data, time series, or streaming datasets preferred.
  • Background in industrial, manufacturing, or aerospace domains preferred.
  • Proficiency with data visualization and storytelling tools (Power BI, Plotly, Databricks dashboards) preferred.
  • Certifications in Databricks, Azure, AWS, or GCP data/ML services preferred.
  • Competitive Salary
  • Health, Dental and Vision Insurance
  • Health Savings Accounts (HSA) with Employer Contribution
  • Flexible Spending Accounts
  • Long and Short-Term Disability
  • Life Insurance
  • Voluntary Benefits
  • Employee Assistance Program
  • Paid Parental Leave
  • Wellness Incentives
  • Vacation and Holiday Pay
  • 401(k) Retirement Plan with Employer Match
  • Employee Stock Purchase
  • Training and Advancement Opportunities
  • Tuition Reimbursement
  • Birthdays Off
  • Philanthropic Opportunities
  • Referral Program
  • Partial Gym Membership Paid
  • Team Building Events
  • Discount Programs
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