The Role
Lead end-to-end ML lifecycle from research to production, design scalable ML systems and pipelines, integrate models with backend services, monitor deployed models, mentor team members, automate processes, and communicate results to stakeholders.
Summary Generated by Built In
We’re looking for a talented Data Scientist to join our AI Research & Growth Team!
Key Responsibilities
- Lead the entire machine learning model lifecycle, from initial research and hypothesis testing to production deployment and maintenance
- Translate complex business goals into well-defined data science problems and quantifiable metrics
- Design and develop robust, scalable machine learning systems from scratch, including data analysis, annotation, and processing pipelines
- Contribute to the overall system architecture and integrate ML models with existing backend services and infrastructure
- Monitor and maintain deployed models, proactively identifying and addressing issues like concept drift to ensure consistent performance
- Support the development and growth of other team members through mentorship and participation in onboarding programs
- Drive continuous improvement by automating repetitive tasks and proposing innovative solutions that lead to significant business impact
- Communicate complex technical concepts and findings clearly and concisely to both technical and non-technical stakeholders
Skills, Knowledge and Expertise
- Previous experience in a data science or machine learning role
- An academic background in a quantitative field such as Computer Science, Mathematics, or a related discipline will be a plus
- Expert-level proficiency in Python and its core data science libraries (e.g., Pandas, NumPy, Scikit-learn, PyTorch)
- Deep expertise in classic machine learning and deep learning techniques, with a strong understanding of advanced mathematics relevant to these fields
- Experience with ML system design and MLOps practices for building, testing, deploying, and monitoring models in a production environment
- Proven experience with event systems, deployment environments, and maintaining production services
- Familiarity with technologies for streaming, batch, and async data processing. Proficiency in at least one specialized ML domain (e.g., NLP, Computer Vision, Tabular ML, Graph Neural Networks)
- Strong understanding of software system design principles and the ability to contribute to architectural discussions
- Experience in experimental design to validate hypotheses and measure the effectiveness of solutions
- A solid grasp of security, risk, and control concepts in a production environment
Why join us
- Help us challenge injustice by creating fair choices for millions of people across 1100+ cities in 48 countries.
- Develop your professional skills with access to mentoring, career consulting, and learning programs.
- Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program.
- Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects.
- Work alongside people who take initiative, speak openly, and challenge themselves to grow.
- Improve your language skills through co-financed courses and internal speaking clubs.
Final benefits may vary depending on the location.
About
inDrive is a global tech company on a mission to challenge injustice. We started in 2012 in the coldest city on Earth, when a group of friends created a way for people to agree on fair ride prices. That idea grew into one of the world’s top ride-hailing apps, now with 360M installs across 48 countries.Today, we offer more than rides: from freight and delivery to intercity travel and financial services, all designed to put people first. Our goal is to positively impact 1 billion lives by 2030. Through inVision, our non-profit arm, we support education, entrepreneurship, and equality in underserved communities.Ready to ignite your inner drive?
Skills Required
- Previous experience in a data science or machine learning role
- Academic background in a quantitative field (Computer Science, Mathematics, related)
- Expert-level proficiency in Python and core data science libraries (Pandas, NumPy, Scikit-learn, PyTorch)
- Deep expertise in classical machine learning and deep learning techniques and advanced mathematics
- Experience with ML system design and MLOps practices for building, testing, deploying, and monitoring models
- Proven experience with event systems, deployment environments, and maintaining production services
- Familiarity with streaming, batch, and async data processing technologies
- Proficiency in at least one specialized ML domain (e.g., NLP, Computer Vision, Tabular ML, Graph Neural Networks)
- Strong understanding of software system design principles and ability to contribute to architecture
- Experience in experimental design to validate hypotheses and measure effectiveness
- Solid grasp of security, risk, and control concepts in a production environment
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The Company
What We Do
inDrive is a global IT and transportation platform inDrive is one of the world’s fastest growing online ride-hailing services. Its services are available in over 749 cities in 46 countries throughout the world. The Company’s app has been downloaded over 150 million times. inDrive offers other services, including intercity transportation, freight and cargo services, as well as delivery services in different markets of operations. inDrive is based in Mountain View, California, and operates regional hubs in the Americas, Asia, the Middle East, Africa and the countries of the CIS, and employs over 2,000 people. In early 2021, inDrive achieved unicorn status after closing a $140m investment round with Insight Partners, General Catalyst, and Bond Capital, which valued the company at $1.23 billion.
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