Data Scientist

Data Scientist, US - East Coast 

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

This role presents an excellent opportunity for a proactive and analytical Data Scientist with approximately three years of professional experience, eager to apply and expand their expertise in a dynamic, data-driven environment. The individual will serve as a key contributor to our data science initiatives, working closely with the Director of Data Science, senior data scientists, and various cross-functional teams. The primary objective will be to transform complex raw data into actionable insights that directly drive strategic business decisions and improve operational efficiency. This position offers significant opportunities for hands-on machine learning model development, in-depth data analysis, and active participation in the full lifecycle of data science projects. All of these contributions will be made while benefiting from direct mentorship and a clear professional growth path within the team.

What You'll Do

Data Collection, Cleaning, and Preprocessing

• The Data Scientist will systematically gather, clean, and preprocess large, often complex and varied, datasets from diverse primary and secondary sources. This ensures high data quality, consistency, and integrity, which is fundamental for subsequent analysis and accurate model building. The role requires implementing robust data wrangling techniques, including identifying and handling missing values, outliers, and inconsistencies, to transform raw data into a suitable and optimized format for analytical and modeling purposes. This foundational work is critical, as the reliability of any subsequent analysis or model hinges on the quality of the input data.   

Exploratory Data Analysis (EDA) and Hypothesis Testing

• The individual will conduct thorough exploratory data analysis to uncover hidden patterns, significant trends, and critical anomalies within datasets, leading to the generation of insightful hypotheses. This involves applying appropriate statistical tools and rigorous techniques to validate these hypotheses, derive actionable conclusions, and inform data-driven decision-making processes across various business functions. The emphasis here is on translating raw data into meaningful observations that can guide strategic choices.   

Machine Learning Model Development and Implementation

• A core responsibility involves collaborating effectively with the Director of Data Science and senior data scientists to design, develop, train, and fine-tune various machine learning models. These models will address tasks such as classification, regression, clustering, and forecasting. The Data Scientist will also assist in the seamless implementation and deployment of these predictive and statistical models into production environments, with a focus on ensuring their scalability, efficiency, and reliability. This includes designing and executing experiments to rigorously test model performance, optimize hyperparameters, and select the most appropriate algorithms to maximize accuracy and efficiency.   

Data Visualization and Reporting

• The Data Scientist will be responsible for creating clear, compelling, and intuitive data visualizations, interactive dashboards, and detailed reports. These outputs are essential for effectively communicating complex findings and insights to both technical and non-technical stakeholders. A key aspect of this responsibility is the ability to translate sophisticated technical results and statistical concepts into clear, concise, and actionable recommendations that can be readily understood and utilized by business teams.   

Collaboration and Communication

• This role requires working in close partnership with data engineers to meticulously define data requirements, construct robust data pipelines, and ensure the necessary infrastructure and tools are in place to support model training and evaluation. The Data Scientist will also actively engage with cross-functional teams, such as product, marketing, and operations, and business stakeholders to deeply understand their challenges, gather detailed requirements, and integrate data insights seamlessly into broader business strategies. Proactive participation in team meetings, presenting project progress, and discussing findings will ensure that data science efforts are consistently aligned with overarching organizational objectives.   

Contribution to Data Strategy and Best Practices

• Under the direct guidance and oversight of the Director of Data Science, the Data Scientist will contribute to the establishment and promotion of best practices in data quality, experimental design, and model reproducibility. The role also involves proactively identifying and proposing opportunities for automation and optimization of existing data processes to enhance efficiency, reduce manual effort, and increase overall impact.

You Have

• A minimum of 3+ years of demonstrable professional experience in a Data Scientist, Data Analyst, or a closely related quantitative role. This experience should include a proven track record of applying analytical techniques to solve real-world problems. Additionally, experience working with large, diverse datasets and contributing to data-driven projects from their conception to the delivery of insights is essential.
• Exceptional ability to dissect complex business problems, identify underlying causes, and develop innovative, data-driven solutions.
• Excellent verbal and written communication skills are essential, with the proven ability to effectively convey complex technical concepts and data insights to diverse audiences, including non-technical business stakeholders and senior leadership.
• Demonstrated ability to work effectively and contribute positively within a collaborative team environment, fostering open communication, sharing knowledge, and supporting collective goals.
• Meticulous attention to detail and a strong commitment to ensuring data accuracy, quality, and the robustness of analytical outputs.

Technical Skills

• Proficiency in Programming Languages: A strong command and hands-on proficiency in Python (including key libraries such as Pandas, NumPy, and Scikit-learn) and/or R are necessary for data manipulation, statistical analysis, and machine learning model development.
• Database Management & SQL: Expert-level proficiency in SQL is required for efficient querying, extraction, and management of data from relational databases. Familiarity with database concepts and schemas is also essential.   
• Statistical Analysis & Modeling: A solid foundational understanding and practical application of statistical concepts, including hypothesis testing, A/B testing, regression analysis, probability distributions, and statistical significance, are crucial for data analysis and model building.
• Machine Learning Algorithms: Hands-on experience with a variety of supervised and unsupervised machine learning algorithms, such as linear/logistic regression, decision trees, random forest, gradient boosting, and clustering, and their practical application in solving business problems is expected.   
• Data Visualization Tools: Demonstrated experience with data visualization libraries (e.g., Matplotlib, Seaborn, ggplot2) and/or business intelligence tools like Tableau or Power BI is necessary to create clear, insightful, and impactful reports and dashboards.   
• Version Control: Familiarity and practical experience with version control systems, particularly Git, are required for collaborative coding, code management, and ensuring reproducibility of work.

 

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 $100,000 - $130,000 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.