Remote opportunity at
ExpelData Scientist
Expel is seeking a Data Scientist to team up with its Detection and Response Engineering and Security Operations Center groups. The posting frames the work around…
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About This Role
Expel is seeking a Data Scientist to team up with its Detection and Response Engineering and Security Operations Center groups. The posting frames the work around cybersecurity incident detection and investigation, and describes the company as a small, highly transparent startup. The role applies machine learning, statistics and generative AI to make analysts' alerts more accurate and speed up their workflows. The job is about turning messy security data into…
Job Description
Expel is seeking a Data Scientist to team up with its Detection and Response Engineering and Security Operations Center groups. The posting frames the work around cybersecurity incident detection and investigation, and describes the company as a small, highly transparent startup. The role applies machine learning, statistics and generative AI to make analysts' alerts more accurate and speed up their workflows.
The job is about turning messy security data into clear capabilities. The data scientist builds and maintains models, helps operations and engineering deploy, monitor and run machine learning systems, and translates results into guidance the business can act on. The position also supports new data science projects, encourages experimentation and continual learning, and offers a platform for blog posts and conference talks about the work.
Required skills include strong Python (pandas, NumPy, scikit-learn) and SQL for modeling, a working grasp of statistics such as distributions, hypothesis testing and probability, and practical knowledge of data engineering and cloud deployment. Three or more years in data science is preferred, including building models and summarizing findings for stakeholders. A quantitative degree (math, statistics or CS), or documented AI/ML experience in its place, is expected. The base salary range is $118,400 to $171,700 USD plus bonus eligibility and equity, and the company's main target band is $135,000 to $160,000, set by experience, ability and market benchmarks. The role is remote and open only to people with U.S. work authorization, and visa sponsorship is not offered.
Responsibilities
- Make analysts' triage more accurate and quicker through analytics, machine learning and generative AI.
- Coordinate with operations, engineering and service delivery to put machine learning systems into production and keep them running.
- Convert analytical results into plain guidance for the business.
- Keep existing models current and help launch new data science efforts.
- Cultivate a habit of experimentation and steady improvement.
- Share expertise publicly through blog posts and conference talks.
Requirements
- Strong Python (pandas, NumPy, scikit-learn) and SQL for model building.
- Working knowledge of statistics, including distributions, hypothesis testing and probability.
- Grasp of data engineering and experience with cloud deployment practices.
- Three or more years of data science work, including building models and summarizing results (preferred).
- Quantitative degree (math, statistics or CS), or documented AI/ML experience in its place.
- Ability to explain technical data science ideas to people outside the field.
- Comfort collaborating across the company on research and innovation.
Core Skills
Benefits
- Unlimited PTO.
- Equity for every employee.
- Flexibility in work location.
- Parental leave of up to 24 weeks.
- Strong health coverage.
Frequently Asked Questions
Answers are based only on the employer’s listing; where it doesn’t say, neither do we.
Is it remote?
The posting is marked remote and mentions location flexibility.
What is the pay?
The base range is $118,400 to $171,700 USD, plus bonus eligibility and equity; the main target band is $135,000 to $160,000.
Is visa sponsorship offered?
No. Only candidates who already have U.S. work authorization are considered, and visas are not sponsored.
What experience is preferred?
Three or more years in data science, plus a quantitative degree or documented AI/ML experience.
Sample Interview Questions
AI-generated questions tailored to this specific role — a preview of the full practice set.