Cybersecurity Lead Jobs
Cybersecurity Lead jobs are open across financial services, healthcare, defense contracting, and technology, from mid-level practitioner to senior leadership, with specializations in cloud security, threat intelligence, and compliance program management. Find a role that fits from the openings below and apply directly.
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As a Cybersecurity AI/ML Lead - Data Scientist - Data Scientist at JPMorgan Chase within the Cybersecurity & Technology Controls, you will be an integral part of a team that develops advanced analytical and machine learning solutions to address complex cybersecurity and technology risk challenges. As a core technical contributor, you will help design and deliver scalable, auditable, and data-driven solutions that support our Cyber Operations teams.
You'll be conducting data analysis, statistical modeling, machine learning, and deep learning techniques to solve cybersecurity and technology risk problems. You will be able to prepare and analyze complex datasets, develop and evaluate models, and communicate findings clearly to technical and business stakeholders. You'll understand when Generative AI, transformer architectures, and related techniques are appropriate for applied security use cases.
Job responsibilities
- Partner with stakeholders, business leaders, cybersecurity engineers, and data engineers to understand security needs, define use cases, and acquire the data required to address them.
- Perform exploratory data analysis on security and technology datasets, identify meaningful patterns, and communicate findings to stakeholders.
- Select, develop, and evaluate statistical, machine learning, deep learning models that are appropriate for cybersecurity use cases and business outcomes.
- Prepare model-ready datasets through feature engineering, data quality assessment, and other data preparation techniques.
- Leads reuse-first adoption of enterprise-authorized AI capabilities within the work environment to accelerate data architecture and model analysis and strategic decisioning, with human-in-the-loop validation and appropriate handling of sensitive data.
- Establishes portfolio-level guardrails for AI-assisted and agentic workflows used in data engineering design and delivery, including traceability/auditability and control expectations aligned to resiliency and security standards.
- Support model governance by documenting model selection, interpretability, testability, performance, limitations, and results.
- Design, build, review, debug, and maintain secure, high-quality production code for analytical and machine learning solutions.
- Contribute to security control effectiveness by applying industry insights, internal standards, and regulatory expectations to improve security processes and protocols.
- Add to a team culture of diversity, equity, inclusion, and respect.
Required qualifications, capabilities, and skills
- Obtain 5 plus years of experience with formal training or certification in security engineering concepts
- Working knowledge of probability, statistics, statistical distributions, and their application to cybersecurity or technology risk use cases.
- Advanced Python skills, including Pandas, SQL, and data visualization tools such as Matplotlib, Seaborn, or Plotly.
- Experience leading teams in the safe use of enterprise-authorized AI capabilities within the work environment for security engineering workflows, including validation habits and awareness of data sensitivity.
- Ability to review and validate AI-assisted security recommendations before adoption, escalating uncertainty and ensuring outcomes align to security, resiliency, and auditability expectations.
- Experience using notebooks such as Jupyter, SageMaker, or VS Code to analyze data, document methods, and communicate results.
- Working knowledge of Scikit-Learn for classification, regression, and clustering models, plus machine learning or deep learning frameworks such as PyTorch.
- Experience preparing complex datasets for modeling, including data cleaning, feature engineering, and data quality assessment.
- Ability to explain model selection, interpretability, performance metrics, and limitations verbally and in writing.
- Proficiency with Software Development Life Cycle, CI/CD practices, application resiliency, and secure software delivery.
- In-depth knowledge of the financial services industry and related IT systems.
Preferred qualifications, capabilities, and skills
- Bachelor's degree in Data Science, Mathematics, Statistics, Econometrics, Computer Science, or a related field, plus 3+ years of applied data science experience.
- Experience with TCP/IP networking, cybersecurity technologies, and security-related telemetry.
- Experience monitoring models in production and identifying data quality, drift, or performance issues.
- Experience deploying statistical or machine learning models in production environments, including AWS SageMaker.
- Working knowledge of Large Language Models, natural language models, vector embeddings, and responsible AI practices such as fairness, reliability, and safety.
ABOUT US
We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans
ABOUT THE TEAM
Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we're setting our businesses, clients, customers and employees up for success.
As a Cybersecurity AI/ML Lead - Data Scientist - Data Scientist at JPMorgan Chase within the Cybersecurity & Technology Controls, you will be an integral part of a team that develops advanced analytical and machine learning solutions to address complex cybersecurity and technology risk challenges. As a core technical contributor, you will help design and deliver scalable, auditable, and data-driven solutions that support our Cyber Operations teams.
You'll be conducting data analysis, statistical modeling, machine learning, and deep learning techniques to solve cybersecurity and technology risk problems. You will be able to prepare and analyze complex datasets, develop and evaluate models, and communicate findings clearly to technical and business stakeholders. You'll understand when Generative AI, transformer architectures, and related techniques are appropriate for applied security use cases.
Job responsibilities
- Partner with stakeholders, business leaders, cybersecurity engineers, and data engineers to understand security needs, define use cases, and acquire the data required to address them.
- Perform exploratory data analysis on security and technology datasets, identify meaningful patterns, and communicate findings to stakeholders.
- Select, develop, and evaluate statistical, machine learning, deep learning models that are appropriate for cybersecurity use cases and business outcomes.
- Prepare model-ready datasets through feature engineering, data quality assessment, and other data preparation techniques.
- Leads reuse-first adoption of enterprise-authorized AI capabilities within the work environment to accelerate data architecture and model analysis and strategic decisioning, with human-in-the-loop validation and appropriate handling of sensitive data.
- Establishes portfolio-level guardrails for AI-assisted and agentic workflows used in data engineering design and delivery, including traceability/auditability and control expectations aligned to resiliency and security standards.
- Support model governance by documenting model selection, interpretability, testability, performance, limitations, and results.
- Design, build, review, debug, and maintain secure, high-quality production code for analytical and machine learning solutions.
- Contribute to security control effectiveness by applying industry insights, internal standards, and regulatory expectations to improve security processes and protocols.
- Add to a team culture of diversity, equity, inclusion, and respect.
Required qualifications, capabilities, and skills
- Obtain 5 plus years of experience with formal training or certification in security engineering concepts
- Working knowledge of probability, statistics, statistical distributions, and their application to cybersecurity or technology risk use cases.
- Advanced Python skills, including Pandas, SQL, and data visualization tools such as Matplotlib, Seaborn, or Plotly.
- Experience leading teams in the safe use of enterprise-authorized AI capabilities within the work environment for security engineering workflows, including validation habits and awareness of data sensitivity.
- Ability to review and validate AI-assisted security recommendations before adoption, escalating uncertainty and ensuring outcomes align to security, resiliency, and auditability expectations.
- Experience using notebooks such as Jupyter, SageMaker, or VS Code to analyze data, document methods, and communicate results.
- Working knowledge of Scikit-Learn for classification, regression, and clustering models, plus machine learning or deep learning frameworks such as PyTorch.
- Experience preparing complex datasets for modeling, including data cleaning, feature engineering, and data quality assessment.
- Ability to explain model selection, interpretability, performance metrics, and limitations verbally and in writing.
- Proficiency with Software Development Life Cycle, CI/CD practices, application resiliency, and secure software delivery.
- In-depth knowledge of the financial services industry and related IT systems.
Preferred qualifications, capabilities, and skills
- Bachelor's degree in Data Science, Mathematics, Statistics, Econometrics, Computer Science, or a related field, plus 3+ years of applied data science experience.
- Experience with TCP/IP networking, cybersecurity technologies, and security-related telemetry.
- Experience monitoring models in production and identifying data quality, drift, or performance issues.
- Experience deploying statistical or machine learning models in production environments, including AWS SageMaker.
- Working knowledge of Large Language Models, natural language models, vector embeddings, and responsible AI practices such as fairness, reliability, and safety.
ABOUT US
We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans
ABOUT THE TEAM
Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we're setting our businesses, clients, customers and employees up for success.
Cybersecurity Lead Jobs by Experience Level
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Find Cybersecurity Lead JobsCybersecurity Lead Job Market
Who's Hiring
Top Industries Hiring
- Consulting & Professional Services
- Energy
- Airlines
- Aerospace & Defense
- Accounting & Auditing
What Employers Look For
The qualifications that appear most often in cybersecurity lead jobs.
- Seven or more years of progressive cybersecurity experience with at least two in a leadership role
- Hands-on proficiency with SIEM platforms such as Splunk, Microsoft Sentinel, or IBM QRadar
- Active CISSP, CISM, or equivalent enterprise security certification
- Experience developing and maintaining security policies aligned to NIST, ISO 27001, or SOC 2 frameworks
- Proven ability to lead incident response efforts and manage post-incident reviews
- Bachelor's degree in computer science, information security, or a closely related field
Tips for Your Cybersecurity Lead Job Search
Tailor your resume to the threat model
Hiring managers scan for evidence you've owned a specific threat environment, whether that's cloud-native, OT/ICS, or regulated industries. Name the frameworks you've applied, the environments you've defended, and the incidents you've led from detection to remediation.
Certify for the roles you target
CISSP covers a broad leadership audience, but roles in federal contracting lean heavily on CISM or CASP+, while cloud-heavy positions prioritize CCSP or AWS Security Specialty. Match your active certifications to the cert stack listed in the job description before you apply.
Quantify program impact on your resume
Vague claims about 'improving security posture' won't differentiate you. Replace them with concrete outcomes: reduced mean time to detect, number of vulnerabilities remediated in a cycle, or audit findings closed. Reviewers in this field are trained to spot unsubstantiated claims.
Apply early to roles that fit
Migrate Mate lists cybersecurity lead openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Prepare for a technical leadership interview split
Cybersecurity lead interviews typically divide time between hands-on technical depth and people or program management scenarios. Practice articulating how you set team priorities during an active incident and how you communicate risk trade-offs to non-technical executives.
Negotiate around total compensation and scope
Security leadership roles vary widely in budget authority, team size, and vendor contract ownership. Before you accept an offer, clarify reporting lines, headcount, and whether you control the security tool budget, since those factors define the actual seniority of the role.
Cybersecurity Lead Jobs: Frequently Asked Questions
Which companies are hiring the most cybersecurity leads?
The companies hiring the most cybersecurity leads right now include JPMorganChase, Goldbelt, and MITRE, with the largest share of openings in Virginia, Illinois, and Maryland, based on current listings on Migrate Mate as of September 2026. Demand is concentrated in financial services, defense contracting, and large technology firms with regulated data environments.
How many cybersecurity lead jobs are remote?
About 61% of cybersecurity lead openings are fully remote or hybrid as of September 2026, though on-site requirements vary significantly by industry. Roles focused on governance, risk, and compliance or cloud security architecture tend to carry the most remote flexibility, while positions tied to on-premises infrastructure or government facilities typically require an in-person presence.
How do you become a cybersecurity lead?
Start by building deep technical experience in at least one security domain such as network defense, cloud security, or incident response. Move into a senior individual contributor role where you own security programs end to end. Earn a recognized leadership certification like CISSP or CISM, demonstrate you can manage projects and communicate risk to business stakeholders, and take on team lead or program ownership responsibilities before targeting formal lead titles.
Can you get hired as a cybersecurity lead with limited experience?
Getting hired as a cybersecurity lead with limited experience is difficult because most employers treat the role as a senior-level position requiring demonstrated incident ownership and program management. You can accelerate your path by leading a security function at a smaller organization, taking on incident command responsibilities in your current role, earning a CISSP or CISM certification, and building a portfolio of documented security improvements you drove from start to finish.
What does the cybersecurity lead interview process look like?
The cybersecurity lead interview process typically runs three to five rounds. An initial recruiter screen is followed by a technical interview covering threat detection, vulnerability management, or architecture decisions relevant to the company's environment. A leadership or behavioral round focuses on how you manage teams and communicate risk. Many employers add a case study or written exercise asking you to assess a mock security scenario, and a final round with senior leadership or the CISO usually closes the process.
Where can I find and apply to cybersecurity lead jobs?
You can find and apply to cybersecurity lead jobs on Migrate Mate, which lists current openings from employers across the United States. Search the listings for roles that match your experience level, industry background, and preferred location or remote arrangement, then apply directly to each opening that fits.
See All 99 Cybersecurity Lead Jobs
Find roles that match your experience and apply in just a few clicks.
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