Scan your resume against ATS criteria for this Staff Applied Scientist- Recommendation Systems role at Glance.
Glance is an intelligent shopping agent, redefining the commerce experience. Powered by proprietary agentic intelligence and generative AI, Glance delivers a hyper-personalized consumer experience across mobile and TV — shaping the new era of shopping. Glance is operated by Glance InMobi Pte. Ltd., a non-consolidated subsidiary of global technology leader InMobi, and is backed by Mithril Capital, Google and Jio Platforms. To learn more, visit glance.com.
InMobi Group is a global technology company shaping the future of agentic commerce and advertising. Through its ecosystem of businesses — including InMobi Advertising and flagship consumer platform Glance — InMobi leverages data, machine learning, and generative AI to help brands reach audiences more precisely and consumers discover products more intuitively. Glance, which is pioneering new models of agentic commerce, is owned and operated by Glance InMobi Pte. Ltd., a non-consolidated subsidiary of InMobi Pte. Ltd.
InMobi Advertising, part of global technology company InMobi, is an agentic advertising platform helping brands and merchants achieve their business outcomes. Through its proprietary intelligence, AI-led solutions, and vast consumer reach — including flagship consumer platform Glance — InMobi Advertising delivers the omnichannel performance defining what's next in advertising and commerce. Glance is owned and operated by Glance InMobi Pte. Ltd., a non-consolidated subsidiary of InMobi Pte. Ltd. To learn more, visit advertising.inmobi.com.
Founded in 2019, Glance is a consumer technology company that operates disruptive digital platforms including Glance, Roposo, and Nostra. Glance’s ’smart lock screen’ inspires consumers to make the most of every moment by surfacing relevant experiences without the need for searching and downloading apps. Glance Lock Screen is currently available on over 450 million smartphones worldwide. Roposo is a LIVE platform that is revolutionizing live experiences, through a unique, immersive, creator-led approach. Nostra is the largest gaming platform in India and Southeast Asia, offering gamers engaging ways to discover, play, watch, learn and compete.
Headquartered in Singapore, Glance is an unconsolidated subsidiary of InMobi Group and is funded by Jio Platforms, Google, and Mithril Capital. For more information visit glance.com, nostra.gg, and http://roposo.com/ roposo.com
At Glance, we walk the talk – free yourself, dream big, and chase your passion! On joining, you’ll have opportunities to make an immediate impact on mission-critical projects, as you work with highly capable and ambitious peer groups.
Be rewarded for your autonomy even as you collaborate. Ideate, innovate, and inspire by leveraging bleeding-edge tech to disrupt consumer experiences.
While you work, we’ll take care of nourishing your body, mind, and soul. This includes daily meals, gym, trainings, tech tools, and regular unwind sessions. Also, feel free to bring your kids – even the furry – to the office!
As a Data Scientist – Recommendation Systems, you will own and drive high-impact ML systems powering personalization across Glance products.
Design, build, and deploy large-scale recommendation and personalization models using diverse, high-volume data sources.
Lead rapid experimentation—from hypothesis formulation to offline evaluation and A/B testing—balancing speed, rigor, and business impact.
Develop and productionize end-to-end ML pipelines, including data preparation, feature engineering, model training, evaluation, and monitoring.
Partner closely with Product, Engineering, Design, UX, and Business teams to translate product goals into scalable ML solutions.
Monitor model health and performance, applying statistical techniques to ensure robustness and long-term effectiveness.
Explore and prototype new ML techniques to improve relevance, engagement, and monetization.
Act as a technical interface for stakeholders, clearly articulating trade-offs, results, and next steps.
Contribute to Glance’s thought leadership through blogs, case studies, and industry conference talks.
Deep expertise in Machine Learning, Data Science, and Recommendation Systems at scale.
Strong applied understanding of experimentation, metrics, and causal reasoning in real-world systems.
Ability to take models from idea → prototype → production → business impact.
10+ years of industry experience in ML/Data Science building large-scale recommendation or personalization systems.
Hands-on experience applying techniques from ML, Deep Learning, NLP, Reinforcement Learning, Time Series, and Statistics.
Strong programming skills in Python with production-quality code practices.
Experience with big data ecosystems, especially Apache Spark.
Familiarity with cloud platforms such as AWS, GCP (Vertex AI), or Azure.
Experience operating in identity-constrained / privacy-aware environments (e.g., iOS/Android, identity-less systems) is a plus.
Excellent communication skills—able to explain complex technical ideas clearly to non-technical stakeholders.
High curiosity, strong problem-solving ability, and a bias toward learning and experimentation.
Bachelor’s or Master’s degree in a quantitative field such as Computer Science, Electrical Engineering, Statistics, Mathematics, Operations Research, Economics, Analytics, or Data Science.
PhD is a plus, but not mandatory.
We value diverse academic backgrounds—great data scientists come from many disciplines.
"Glance collects and processes personal data such as your name, contact details, resume and other information that may contain personal data for the purpose of processing your application. Glance utilizes Greenhouse, a third-party platform. Please review Greenhouse's Privacy Policy to understand how the data collected from you is processed and managed. By clicking on 'Submit Application', you acknowledge and agree to the above privacy terms. Should you have any privacy concerns, you may contact us through the details mentioned in your application confirmation email."
How to apply for Staff Applied Scientist- Recommendation Systems at Glance?
Click the "Apply on Company Website" button on this page to submit your application directly on the employer's official portal.
What is the salary for this role?
Salary details will be discussed during the interview.
What experience is required?
10+ years of experience is required.
Is this position still open?
Yes, currently active and accepting applications.
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Staff Applied Scientist- Recommendation Systems
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