高级数据科学家 - 内容
Senior Data Scientist - Content
About Engine
Engine is the AI-native platform for intelligent travel. For a decade, Engine has built the proprietary technology and supply behind modern business travel, serving over 40,000 customers and nearly 2 million travelers, along with leading travel and AI companies that build on Engine's infrastructure. One system powers business travel, group travel, human agents, and AI agents.
That work has earned recognition as one of Fast Company's Best Workplaces for Innovators (2025), TravelTech's Reservation Platform of the Year (2026), and one of Built In's Best Places to Work (2020–2026).
We're looking for bold, ambitious people to help redefine how businesses manage and experience travel. Working here, you can expect exponential growth, an ambitious pace, full ownership, and high-caliber colleagues who push you to do the best work of your career. Every hire raises the bar.
Come outpace the ordinary and build the future of travel with us.
Your Mission
Establishing and maintaining high-quality data infrastructure, data assets, and data science capabilities are critical for the company's continued success. We have and will continue to invest heavily to leverage data science and machine learning to drive strategic and business decisions, power key product features, and solve problems that directly improve our customers’ experience and the strength of our business. As a Data Scientist at Engine, you’ll play a vital role in an environment where innovation meets collaboration. Here’s what you’ll take charge of:
- Develop and implement data science strategies to enhance key machine learning models and services, including lead scoring, churn modeling, pricing, personalization, and fraud detection.
- Collaborate with engineering and business stakeholders to ensure actionable insights, effective implementation, and measurable business impact.
- Drive end-to-end data science initiatives,from gathering and analyzing data to feature engineering, model selection/training, inference, and monitoring.
- Enhance data infrastructure and analytics capabilities by working closely with our data infrastructure and analyst teams.
- Effectively communicate findings to both technical and non-technical audiences, ensuring transparency and alignment across teams.
What You’ll Bring to Engine
We’re looking for someone who’s ready to make an impact and grow alongside us:
- Experience: 5+ years of industry experience as a Data Scientist/ML Engineer in high-growth environments.
- Technical Skills: Strong expertise in machine learning algorithms and statistical modeling, with proficiency in Python (including scikit-learn, numpy, and pandas) and SQL. Experience with Snowflake and Streamlit is a plus.
- Education: MS/PhD in a quantitative discipline such as Mathematics, Statistics, Operations Research, Economics, Engineering, or Computer Science.
- Problem-Solving Mindset: A bias toward simple, effective ML solutions before diving into complex approaches.
- Communication Skills: Ability to present findings clearly to both technical and non-technical stakeholders.
- Adaptability: Thrive in a fast-paced, dynamic environment with a willingness to take initiative and drive meaningful impact.
Applications for this role will be accepted through 04/026/2026 or until the role is filled. We encourage you to apply early, as we may begin reviewing applications before the deadline.
Compensation
Our compensation packages are based on several factors, including your experience, expertise, and location. In addition to a competitive base salary, all roles receive equity. Depending on the role, total compensation may also include an annual bonus. Your recruiter will share your complete compensation package as you move through the process.
Base Pay Range
$170,000—$200,000 USD
The Engine Edge: Perks & Compensation
We believe in rewarding great work with great benefits:
- Compensation: Competitive base pay tied to role and experience, with equity for all employees. Some roles are also eligible for bonuses or commissions.
- Benefits: Check out our full list at
- Environments for Success: Different roles have different needs in terms of the environments that drive success which is why we have a hybrid-hub model. Whether you are in one of our amazing offices or fully remote, we'll make sure you have what you need to succeed.
Perks and benefits may vary based on employment type, location, and more
Originally posted on Himalayas