Jobs / United States / Everquote INC
Data Scientist
Everquote INC · 🇺🇸 Cambridge, Massachusetts, United States
Sponsorship verdict
Sponsorship possible
One solid signal, not two — worth applying, and worth asking about sponsorship early.
- Employer is on a government sponsor recordThe US Department of Labor certified 8 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest May 2026) — the step every H-1B hire needs first. USCIS also records 6 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
- The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
- No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
- What Everquote INC paid sponsored hires in similar roles2 certified filings for “Senior Quantitative Analyst” (Data Scientists) in MA: $90k–$90k, median $90k. Most were filed at wage level I (100%) — 1 lottery entry, ≈15% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).
- Confirmed live todayWhen a source last listed this job as open.
US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).
A verdict summarises public evidence; it is not legal advice and never a guarantee — the employer and the immigration authority decide. Sign in to factor in where you can already work.
Or apply yourself on the official page →
Sponsor Radar — Everquote INC
The US Department of Labor certified 8 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest May 2026) — the step every H-1B hire needs first. USCIS also records 6 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
Past sponsorship or register membership never guarantees sponsorship for this vacancy or for you. Full Sponsor Radar for Everquote INC →
About the role
Location: Cambridge, MA / Hybrid (This role requires working in-office 3 days per week: Tuesday, Wednesday, and Thursday.) About us: EverQuote is a leading AI-powered growth solutions partner for regulated property and casualty insurance entities, enabling the largest insurance carriers and thousands of agents to maximize customer acquisition across digital channels. Fueled by our proprietary data assets and our AI traffic engine, EverQuote is transforming the way providers attract and engage consumers to grow market share. Joining our team puts you at the forefront of this transformation. You will collaborate with a group of builders to solve complex problems and reshape a massive industry. If you want to drive real-world impact and do the best work of your career, you’ve found your home. We move fast, follow the data, and hold ourselves to high standards. If that's how you work too, this is the role for you. EverQuote is seeking a Data Scientist to join our growing team! As a member of the Data Science team, you will be instrumental in delivering and deploying artificial intelligence and machine learning models that drive Everquote’s long term success. What you'll do: • Work with a cross-functional team to convert business problems into scalable solutions using your knowledge of mathematics, statistics, and machine learning. You will be joining a team of talented and collaborative data scientists and machine learning engineers eager to grow our business and deliver measurable results. You will establish yourself as a technical leader and a valued team member as our team continues to grow. Who you are: • 2+ years of professional experience as a data scientist including experience developing and releasing predictive models to production • Bachelor’s degree in a technical field such as mathematics, statistics, computer science or economics; Master’s degree or PhD in a relevant field preferred. • Demonstrated success turning businesses problems into data problems and developing innovative and unexpected solutions • Ability to explain results to technical and non-technical teammates leveraging your communication skills and data visualization • Demonstrated performance in building machine learning models using standard tools, such as scikit-learn or R, to drive business improvements • Advanced knowledge of applied mathematics and statistics and their common applications in online businesses • Experience with or strong interest in understanding and optimizing online auctions for both bidders and sellers • Experience with or strong interest in optimization using reinforcement learning and contextual multi-armed bandits • Strong skills in statistical and scientific programming in Python, fluent in SQL, proficient with Jupyter notebooks • Experience with packaging your code for deployment and reusability • Passionate about sharing knowledge and mentoring teammates, and communicating designs to technical and non-technical stakeholders • Keen sense about data science technologies, stay on top of industry trends and actively help the team to expand the tech stack • Entrepreneurial mindset, want to grow a business, and love working with an Agile team • Thrive in a fast-paced work environment where everyday contributions have a big impact Education & Experience: • Bachelors degree in a technical field, with an advanced degree in Data Science, Computer Science, Math/Statistics, or a related field strongly preferred • Internship or equivalent professional experience in Data Science/MLE required. At least 2 years of professional experience in Data Science/ML preferred (preferred more strongly for candidates without an advanced degree) • Proven experience building and delivering ML solutions in a production eng environmen