Director of Data Science

Summary

Join Cobalt as the Director of Data Science, a pivotal leadership role overseeing all data science and advanced analytics initiatives. You will guide the development and implementation of data strategies, driving critical business decisions. Lead and empower a team of data scientists and analysts, transforming raw data into actionable insights. Define and refine the data science vision and roadmap, aligning with company goals. Oversee the entire machine learning model lifecycle, from design to deployment and maintenance. Ensure compliance with data privacy regulations and ethical guidelines. Collaborate with cross-functional teams and represent Cobalt externally. Continuously enhance the team's knowledge and capabilities through innovation and experimentation.

Requirements

• A Master's or Ph.D. degree is highly preferred in a quantitative field such as Statistics, Mathematics, Data Science, Physics, or a closely related discipline
• A minimum of 10+ years of progressive, hands-on experience in data analytics, data science, machine learning engineering, or a related analytical field
• At least 3+ years of dedicated experience in a data science leadership role, demonstrating a proven track record of successfully managing, mentoring, and scaling high-performing, cross-functional data science teams
• Demonstrated success in leading and delivering complex, large-scale data science projects from initial conceptualization through to robust production deployment and ongoing maintenance
• Proven experience in managing significant budgets and strategically allocating resources for analytics initiatives to achieve impactful business outcomes in a start-up environment. Lean-forward, be scrappy
• Advanced Analytical & Statistical Skills: Profound expertise in advanced statistical modeling, a wide array of machine learning algorithms (e.g., linear and logistic regression, advanced ensemble models such as Random Forest, XGBoost, CatBoost), deep learning architectures, natural language processing (NLP) techniques, and rigorous experimentation methodologies
• Programming Languages: Advanced proficiency in Python and SQL is absolutely essential
• Big Data Technologies & Cloud Platforms: Extensive hands-on experience with big data technologies (e.g., Hadoop, Spark) and a strong working knowledge of GCP-based data platforms
• MLOps & Data Engineering Concepts: A comprehensive understanding of the end-to-end machine learning pipeline, practical experience with MLOps practices for reliable model deployment and maintenance, strong grasp of data engineering principles, ETL (Extract, Transform, Load) processes, and workflow management platforms
• Data Visualization: Proven proficiency with industry-standard data visualization tools (e.g., Tableau, PowerBI, Python libraries like Matplotlib, Seaborn) and the ability to translate complex data understandings into clear, compelling visual narratives

Responsibilities

• Define, lead, and continuously refine the data science vision, overarching strategy, and multi-year roadmap, ensuring direct alignment with the organization's overarching business goals and clearly defined, measurable outcomes
• Serve as a principal strategic advisor and thought leader, proactively championing the ethical and responsible adoption and pervasive utilization of AI/ML technologies across all relevant organizational functions
• Collaborate intimately with cross-functional teams, including Product, Engineering, Marketing, and Sales, to systematically identify, evaluate, and prioritize high-impact data science opportunities
• Oversee the entire lifecycle of machine learning models, encompassing their conceptual design, rigorous development, comprehensive validation, robust production deployment, continuous monitoring, and iterative improvement
• Drive the development of sophisticated copilot and AI pentester solutions
• Ensure that the data science, engineering, and product management teams build reliable and accurate models, and rigorously selects and applies appropriate evaluation techniques to validate their performance
• Establish, implement, and promote industry-leading best practices in data collection, storage, analysis, data governance, and model reproducibility across all data science projects
• Ensure stringent compliance with all applicable data privacy regulations, security standards (e.g., SOC 2, GDPR, CCPA, specific student data privacy requirements if relevant), and ethical guidelines for data utilization throughout the organization
• Collaborate strategically with Data Engineering teams to design and implement scalable, well-defined data assets, robust feature stores, and precise metrics that support evolving analytical and product requirements
• Serve as a critical liaison and bridge between highly technical teams and business stakeholders, ensuring seamless alignment on strategic priorities, project deliverables, and the demonstrable strategic value of data science initiatives
• Represent the organization effectively in external collaborations, industry conferences, and professional consortia to maintain a leading position at the forefront of data science advancements
• Proactively monitor and integrate understandings from industry trends and emerging technologies (including advanced ML, AI, Deep Learning, Natural Language Processing, and agentic AI) to continuously enhance the team's collective knowledge and elevate the organization's data science capabilities
• Lead and champion experimentation efforts to systematically test, iterate upon, and refine models and user experiences, ensuring continuous evolution aligned with evolving business needs
• Proactively identify opportunities for process automation, optimization of data workflows, and effective mitigation of potential risks inherent in data science projects

Preferred Qualifications

Practical familiarity with other relevant languages such as R, Java, C++, Go, or Scala is highly advantageous

Benefits

• Earn competitive compensation and an attractive equity plan
• Save for the future with a 401(k) program (US)
• Benefit from medical, dental, vision and life insurance (US)
• Wellness stipends
• Work-from-home equipment & wifi stipends
• Learning & development stipends
• Make the most of our flexible, generous paid time off and paid parental leave