Lead Data Scientist

This is a fully remote position, open to applicants in Washington.

📋 Description

• Oversee the design, development, and implementation of sophisticated analytics and machine learning solutions.

• Collaborate with clients and stakeholders to comprehend business goals and convert requirements into analytical strategies.

• Examine large and intricate datasets to reveal insights, identify opportunities, and aid in strategic decision-making.

• Create and validate statistical, predictive, and machine learning models.

• Present technical findings and recommendations to both executive and non-technical audiences.

• Offer technical guidance and mentorship to data scientists, analysts, and cross-functional project teams.

• Work alongside data engineering, product, and business stakeholders to facilitate end-to-end solution delivery.

• Establish best practices for model development, testing, validation, documentation, and performance monitoring.

• Contribute to project planning, solution architecture, estimation, and execution of delivery.

• Assist in business development through technical expertise, solution ideation, and client presentations.

⛳️ Requirements

• 10–15 years of experience in the role of a data scientist.

• Proficient in designing, building, and validating production-grade machine learning models utilizing Python and SQL.

• Proven experience in leading complex analytics projects and influencing technical decision-making.

• Familiarity with building solutions in Azure, particularly with Azure Machine Learning, MLflow, Azure Synapse, and Microsoft Fabric.

• Strong consulting experience with clients and effective stakeholder management skills.

• Outstanding communication and presentation capabilities.

• Experience throughout the complete data science lifecycle, from problem definition to model deployment and adoption.

• Demonstrated success in leading projects within enterprise environments.

• Previous consulting experience and/or background in utilities, energy, infrastructure, asset management, or reliability-focused sectors is highly preferred.

• Experience in developing models for risk, reliability, asset health, anomaly detection, or failure prediction is preferred.

• Experience in supporting model governance, validation, explainability, and operationalization efforts is preferred.

• A Master’s degree or PhD in machine learning, statistics, computer science, data mining, mathematics, or a related quantitative field is preferred.

🏝️ Benefits

• Competitive compensation package.

• Performance-based bonuses and additional incentives for eligible employees.

• Opportunities for training, project involvement, and mentorship.

• A supportive, globally connected work environment.

• Option for remote work.