[Hiring] Data Science Lead at Stralynn Consulting Services, Inc

The Data Science Lead is a visionary architect of advanced analytical strategies, responsible for designing and validating complex AI/Machine Learning pipelines. This role ensures that all models are explainable, ethically sound, and aligned with client expectations and organizational objectives. The Data Science Lead provides technical leadership, mentors a team of data scientists and AI engineers, and oversees the entire lifecycle of predictive and prescriptive models to drive data-driven innovation and insights.

Responsibilities:

• Design, develop, and validate sophisticated forecasting, risk scoring, and anomaly detection models using advanced statistical and machine learning techniques.

• Provide expert supervision and guidance on causal inference methods and intricate machine learning feature engineering processes.

• Strategically manage the development and deployment of predictive modeling solutions across diverse and large-scale datasets.

• Lead and mentor a high-performing team of AI engineers and data scientists, fostering a collaborative and innovative environment.

• Oversee comprehensive model governance frameworks, ensuring explainability, audit trail compliance, and adherence to ethical AI principles.

• Architect and optimize AI/ML pipelines within cloud-based analytical environments (e.g., Databricks, Snowflake).

• Collaborate with business intelligence developers to integrate model outputs into actionable dashboards and reports.

• Drive continuous research and adoption of emerging AI/ML techniques and technologies relevant to the healthcare domain.

• Communicate complex data science concepts and model insights effectively to both technical and non-technical stakeholders.

• Ensure the reproducibility, scalability, and performance of all developed analytical solutions.

  Experience Required:

• 8+ years of progressive experience leading healthcare or public sector AI/Machine Learning teams and projects.
• Extensive hands-on experience in designing, building, and deploying advanced predictive and analytical models.

• Proven track record of managing complex data science initiatives from concept to production.

• Deep understanding of explainable AI (XAI) principles and methodologies.

  Certifications / Education:

• Master’s degree (MS) in Data Science, Computer Science, Statistics, Applied Mathematics, or an equivalent quantitative field.
• Machine Learning/Artificial Intelligence Certifications (preferred).

  Skills:

• Explainable AI (XAI)
• Causal Inference

• Python/R (advanced proficiency)

• Databricks, Snowflake

• Machine Learning Algorithms

• Deep Learning

• Model Governance

• Team Leadership

• Data Architecture

• Problem-Solving