Who We Are

Cobalt was founded on the belief of a fundamental human aspiration: the desire to live better and safer. It all started in 2013, when our founders realized that pentesting can be better. Today our diverse, fully remote team is committed to helping organizations of all sizes with seamless, effective and collaborative Offensive Security Testing that empower organizations to OPERATE FEARLESSLY and INNOVATE SECURELY.

Our customers can start a pentest in as little as 24 hours and integrate with advanced development cycles thanks to the powerful combination of our SaaS platform coupled with an exclusive community of testers known as the Cobalt Core. Accepting just 5% of applicants, the Cobalt Core boasts over 400 closely vetted and highly skilled testers who jointly conduct thousands of tests each year and are at the forefront of identifying and helping remediate risk across a dynamically changing attack surface.

Cobalt is an Equal Opportunity Employer and we strive to build a diverse and inclusive workforce at our company. At Cobalt we aspire to engage with diverse individuals, communities, and organizations in order to continue to nurture our unique rich diverse culture. Join our team, and be your true self to do your best work.
Description

The Director of Data Science position is a pivotal leadership role responsible for overseeing all data science and advanced analytics initiatives across the enterprise. Reporting directly to Cobalt's CTO, the director is responsible for guiding the conceptualization, development, and implementation of comprehensive data strategies that directly drive critical business decisions and align with overarching company objectives.

The successful candidate is responsible for leading, inspiring, and empowering a multidisciplinary team of highly skilled data scientists and analysts from the ground up - identifying strategic opportunities for leveraging data science and integrating data-driven solutions across the organization.

As a lean-forward leader you'll take a hands-on role in transforming raw, complex data into meaningful, actionable understandings that directly propel the company's growth, innovation, and competitive advantage in the world of penetration testing and AI.
What you'll do

Strategic Direction & Roadmap Definition:

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.

Model Development & Operational Oversight:

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.

Data Governance, Quality & Compliance:

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.

Communication & Stakeholder Engagement:

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.

Innovation & Continuous Improvement:

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.

You have

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.

Technical Proficiencies:

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

Why You Should Join Us

Grow in a passionate, rapidly expanding industry operating at the forefront of the Pentesting industry
Work directly with experienced senior leaders with ongoing mentorship opportunities
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)
Leverage stipends for:
- Wellness
- Work-from-home equipment & wifi
- Learning & development
Make the most of our flexible, generous paid time off and paid parental leave

Pay Range Disclosure

Cobalt is committed to fair and equitable compensation practices. The salary range for this role is ($200,000 to $250,000) per year + equity + benefits. A candidate's salary is determined by various factors including, but not limited to, relevant work experience, skills, and certifications. The salary range may differ in other states and may be impacted by proximity to major metropolitan cities.

Cobalt (the "Company") is an equal opportunity employer, and we want the best available persons for every job. The Company makes employment decisions only based on merit. It is the Company's policy to prohibit discrimination in any employment opportunity (including but not limited to recruitment, employment, promotion, salary increases, benefits, termination and all other terms and conditions of employment) based on race, color, sex, sexual orientation, gender, gender identity, gender expression, genetic information, pregnancy, religious creed, national origin, ancestry, age, physical/mental disability, medical condition, marital/domestic partner status, military and veteran status, height, weight or any other such characteristic protected by federal, state or local law. The Company is committed to complying with all applicable laws and providing equal employment opportunities. This commitment applies to all persons involved in the operations of the Company regardless of where the employee is located and prohibits unlawful discrimination by any employee of the Company.

Cobalt is an E-Verify employer. E-Verify is an Internet-based system operated by the Department of Homeland Security (DHS) in partnership with the Social Security Administration (SSA). It allows participating employers to electronically verify the employment eligibility of their newly hired employees in the United States.

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Director of Data Science