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 r