Interested in this Data Scientist role at Bitsight?
Apply Now →Skills & Technologies
About This Role
Bitsight is a cyber risk management leader transforming how companies manage exposure, performance, and risk for themselves and their third parties. Companies rely on Bitsight to prioritize their cybersecurity investments, build greater trust within their ecosystem, and reduce their chances of financial loss.
Built on over a decade of technological innovation, its integrated solutions deliver value across enterprise security performance, digital supply chains, cyber insurance, and data analysis.
- We invented the cyber ratings industry in 2011
- Over 3000 customers trust Bitsight
- Over 750 teammates are dispersed throughout Boston, Raleigh, New York, Lisbon, Singapore, and remote
We are hiring a visionary Principal Data Scientist in a critical senior technical leadership role, to define and execute the future of our ML and AI strategy. Idea candidate is a practitioner with extensive ML/AI product development experience who can accelerate our technological advantage, guide high\-stakes cross\-functional efforts, and directly influence Bitsight's long\-term business and technical strategy. Specifically, this role will be in charge of designing and deploying advanced, production\-grade ML/AI applications within our AI\-driven asset attribution and Graph of Internet Assets (GIA) data engine, leveraging advanced graph technology and ML/AI models to discover complex organization and asset relationships and map internet\-connected assets at a global scale.
Responsibilities:
- Own the ideation and execution of high\-impact ML/AI initiatives that directly advance Bitsight's product strategy and technical roadmap.
- Design, build, and deploy production\-grade ML models and automation systems that support critical business features.
- Develop and maintain end\-to\-end ML pipelines, including data extraction, feature engineering, training, evaluation, deployment, monitoring, and automated feedback and retraining loops.
- Serve as the principal architect for scalable, high\-performance ML/AI components within our cloud\-based distributed systems.
- Analyze large\-scale cybersecurity datasets to identify opportunities for improved classification, detection, and automation.
- Drive the integration of ML/AI outcomes, translating complex findings into clear, actionable product decisions for engineering and business stakeholders.
- Establish and promote best practices for ML/AI development, model operations, and data\-quality standards.
- Mentor technical contributors across teams, elevating technical quality and accelerating development.
- Provide leadership in communicating complex findings and decisions to technical and non\-technical stakeholders, upholding Bitsight’s documentation\-driven culture.
Requirements:
- M.S. or Ph.D. in a quantitative field (e.g., Computer Science, Statistics, Engineering) or equivalent practical experience.
- Extensive experience (8\+ Years for Principal level) delivering ML/AI\-powered product features from concept to production.
- Expertise in Python, SQL, distributed compute environments, and cloud platforms.
- Demonstrated ability to lead complex ML/AI initiatives driving business impact.
- Excellent communication skills, with a track record of influencing cross\-functional stakeholders and leadership.
- Proven capability to bring structure to ambiguous problem spaces and drive them toward actionable, high\-impact outcomes.
Preferred:
- Experience with advanced ML techniques such as deep learning, GNNs, anomaly detection, or probabilistic modeling.
- Experience defining or influencing ML/AI practices and strategies across the business, particularly for Principal\-level candidates.
- Background in cybersecurity, threat intelligence, or large\-scale network analytics.
Belonging \& Inclusion. Bitsight is proud to be an equal opportunity employer. This means we do not tolerate discrimination of any kind and are committed to providing equal employment opportunities regardless of your gender identity, race, nationality, religion, sexual orientation, status as a protected veteran, or status as an individual with a disability.
Culture. We put our people first. Bitsight offers best in class benefits. We devote the same energy to nurturing our company's inclusive culture as we apply to serving our customers' needs. Working at Bitsight will give you the opportunity to fulfill your professional goals and expand your skills.
Open\-minded. If you got to this point, we hope you’re feeling excited about the job description you just read. Even if you don’t feel that you meet every single requirement, we still encourage you to apply. We’re eager to meet people that believe in Bitsight’s mission and can contribute to our team in a variety of ways.
Bitsight also provides reasonable accommodations to qualified individuals with disabilities or based on a sincerely held religious belief in accordance with applicable laws. If you need to inquire about a reasonable accommodation, or need assistance with completing the application process, please email [email protected]. This contact information is for accommodation requests only, and cannot be used to inquire about the status of applications.
Additional Information for United States of America Applicants:
Bitsight is committed to compliance with all fair employment practices regarding citizenship and immigration status.
Bitsight will not discharge, discipline or in any other manner discriminate against any employee or applicant for employment because such employee or applicant has inquired about, discussed, or disclosed the compensation of the employee or applicant or another employee or applicant.
Massachusetts Applicants: *It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.*
Qualified applicants with criminal histories will be considered for employment consistent with applicable law.
This position may be considered a promotional opportunity pursuant to the Colorado Equal Pay for Equal Work Act.
The anticipated hiring base salary range for this position is US$180000 to $205000 annually for US\-based employees. This range reflects the minimum and maximum target for new hire salaries for the position across all US locations, is based on a full\-time work schedule, and is Bitsight’s good faith estimate as of the date of this posting. Within the range, individual pay is determined by work location and additional factors, including job\-related skills, experience, and relevant education or training.In addition to base salary, this role is eligible for participation in a bonus or commission plan and an equity grant. Bitsight also offers a competitive benefits package, including but not but limited to medical, dental, and vision insurance; paid parental leave; flexible time off; a 401(k) plan with employee and company contribution opportunities; life and disability insurance; and tuition reimbursement.
Salary Context
This $180K-$205K range is above the 75th percentile for Data Scientist roles in our dataset (median: $157K across 236 roles with salary data).
View full Data Scientist salary data →Role Details
About This Role
Data Scientists extract insights and build predictive models from data. In the AI era, many roles now include LLM-powered analytics, automated reporting, and integration with generative AI tools. The role has evolved from 'the person who runs SQL queries' to 'the person who builds AI-powered data products.'
Modern data science roles fall into two camps: analytics-focused (insights, dashboards, experimentation) and ML-focused (building predictive models, recommendation systems, NLP features). The best data scientists can operate in both modes. The AI shift means that even analytics-focused roles now involve building automated insight pipelines using LLMs, going well beyond one-off reports.
Across the 3,823 AI roles we're tracking, Data Scientist positions make up 8% of the market. At Bitsight, this role fits into their broader AI and engineering organization.
Data Scientist roles remain in high demand, though the definition keeps shifting. Companies increasingly want candidates who can bridge traditional statistics with modern ML and LLM capabilities. The 'pure insights' data scientist role is consolidating into analytics engineering, while the 'build models' data scientist role is merging with ML engineering.
What the Work Looks Like
A typical week includes: analyzing experiment results for a product feature launch, building a predictive model for customer churn, creating an automated reporting pipeline using LLM-powered summarization, presenting insights to stakeholders, and cleaning data (always cleaning data). The ratio of analysis to engineering varies by company, but expect both.
Data Scientist roles remain in high demand, though the definition keeps shifting. Companies increasingly want candidates who can bridge traditional statistics with modern ML and LLM capabilities. The 'pure insights' data scientist role is consolidating into analytics engineering, while the 'build models' data scientist role is merging with ML engineering.
Skills Required
Python, SQL, and statistical modeling are the foundation. Increasingly, roles want experience with LLMs for data analysis, automated insight generation, and building AI-powered data products. Familiarity with cloud data platforms (Snowflake, BigQuery, Databricks) and ML frameworks (scikit-learn, PyTorch) covers most job requirements.
Experimentation design and causal inference are underrated skills that separate strong candidates. Companies care about whether their product changes cause improvements, and can distinguish causation from correlation. A/B testing methodology, Bayesian statistics, and the ability to communicate uncertainty to non-technical stakeholders are high-value skills.
Good postings specify the data stack, the types of problems you'll work on, and the team structure. Look for companies that differentiate between analytics and ML data science. Vague 'data scientist' postings that list every skill under the sun usually mean the company doesn't know what they need.
Compensation Benchmarks
Data Scientist roles pay a median of $198,000 based on 808 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. Disclosed range: $180K to $205K.
Across all AI roles, the market median is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($275,000) and AI Safety ($274,200). By seniority level: Entry: $97,880; Mid: $165,000; Senior: $227,400; Director: $247,800; VP: $250,000.
Bitsight AI Hiring
Bitsight has 1 open AI role right now. They're hiring across Data Scientist. Based in Boston, MA, US. Compensation range: $205K - $205K.
Location Context
AI roles in Boston pay a median of $215,350 across 442 tracked positions. That's 8% above the national median.
Career Path
Common paths into Data Scientist roles include Data Analyst, Statistician, Quantitative Researcher.
From here, career progression typically leads toward Senior Data Scientist, ML Engineer, AI Product Manager.
Start with statistics and SQL. Build a real analysis project on public data that demonstrates insight generation alongside model building. The market values data scientists who can communicate findings clearly to business stakeholders. If you want to move toward ML engineering, invest in software engineering fundamentals and production deployment skills.
What to Expect in Interviews
Interviews combine statistics, coding, and business acumen. SQL is almost always tested, often with complex joins and window functions. Expect a case study round where you're given a business problem and asked to design an analysis plan. Coding rounds focus on pandas, statistical modeling, and visualization. The strongest differentiator is how well you communicate insights to non-technical stakeholders during presentation rounds.
When evaluating opportunities: Good postings specify the data stack, the types of problems you'll work on, and the team structure. Look for companies that differentiate between analytics and ML data science. Vague 'data scientist' postings that list every skill under the sun usually mean the company doesn't know what they need.
AI Hiring Overview
The AI job market has 3,823 open positions tracked in our dataset. By seniority: 112 entry-level, 1,798 mid-level, 1,516 senior, and 397 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (590 positions). The remaining 3,217 roles require on-site or hybrid attendance.
The market median for AI roles is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($275,000 median, 41 roles); AI Safety ($274,200 median, 55 roles); Research Engineer ($260,000 median, 434 roles).
Data Scientist roles remain in high demand, though the definition keeps shifting. Companies increasingly want candidates who can bridge traditional statistics with modern ML and LLM capabilities. The 'pure insights' data scientist role is consolidating into analytics engineering, while the 'build models' data scientist role is merging with ML engineering.
The AI Job Market Today
The AI job market spans 3,823 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,629), Data Scientist (322), AI Software Engineer (279). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (112) are outnumbered by mid-level (1,798) and senior (1,516) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 397 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (590 positions), with 3,217 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $200,100. Top-quartile roles start at $253,500, and the 90th percentile reaches $307,500. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Engineering Manager roles lead at $275,000 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,979 postings), Aws (1,190 postings), Azure (899 postings), Rag (839 postings), Gcp (726 postings), Pytorch (595 postings), Prompt Engineering (595 postings), Claude (540 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
Get Weekly AI Career Intelligence
Salary data, skills demand, and market signals from 16,000+ AI job postings. Every Monday.