Python
Machine Learning (ML)Job Description: Applied Scientist
Location: Bangalore / Hybrid / Remote
Company: LodgIQ
Industry: Hospitality / SaaS / Machine Learning
About LodgIQ
Headquartered in New York, LodgIQ delivers a revolutionary B2B SaaS platform to the
travel industry. By leveraging machine learning and artificial intelligence, we enable precise
forecasting and optimized pricing for hotel revenue management. Backed by Highgate
Ventures and Trilantic Capital Partners, LodgIQ is a well-funded, high-growth startup with a
global presence.
About the Role
We are seeking a highly motivated Applied Scientist to join our Data Science team. This
individual will play a key role in enhancing and scaling our existing forecasting and pricing
systems and developing new capabilities that support our intelligent decision-making
platform.
We are looking for team members who: ● Are deeply curious and passionate about applying machine learning to real-world
problems. ● Demonstrate strong ownership and the ability to work independently. ● Excel in both technical execution and collaborative teamwork. ● Have a track record of shipping products in complex environments.
What You’ll Do ● Build, train, and deploy machine learning and operations research models for
forecasting, pricing, and inventory optimization. ● Work with large-scale, noisy, and temporally complex datasets. ● Collaborate cross-functionally with engineering and product teams to move models
from research to production. ● Generate interpretable and trusted outputs to support adoption of AI-driven rate
recommendations. ● Contribute to the development of an AI-first platform that redefines hospitality revenue
management.
Required Qualifications ● Bachelor's or Master’s degree or PhD in Computer Science or related field. ● 3-5 years of hands-on experience in a product-centric company, ideally with full model
lifecycle exposure.
Commented [1]: Leaving note here
Acceptable Degree types - Masters or PhD
Fields
Operations Research
Industrial/Systems Engineering
Computer Science
Applied Mathematics
● Demonstrated ability to apply machine learning and optimization techniques to solve
real-world business problems.
● Proficient in Python and machine learning libraries such as PyTorch, statsmodel,
LightGBM, scikit-learn, XGBoost
● Strong knowledge of Operations Research models (Stochastic optimization, dynamic
programming) and forecasting models (time-series and ML-based).
● Understanding of machine learning and deep learning foundations.
● Translate research into commercial solutions
● Strong written and verbal communication skills to explain complex technical concepts
clearly to cross-functional teams.
● Ability to work independently and manage projects end-to-end.
Preferred Experience
● Experience in revenue management, pricing systems, or demand forecasting,
particularly within the hotel and hospitality domain.
● Applied knowledge of reinforcement learning techniques (e.g., bandits, Q-learning,
model-based control).
● Familiarity with causal inference methods (e.g., DAGs, treatment effect estimation).
● Proven experience in collaborative product development environments, working closely
with engineering and product teams.
Why LodgIQ?
● Join a fast-growing, mission-driven company transforming the future of hospitality.
● Work on intellectually challenging problems at the intersection of machine learning,
decision science, and human behavior.
● Be part of a high-impact, collaborative team with the autonomy to drive initiatives from
ideation to production.
● Competitive salary and performance bonuses.
● For more information, visit https://www.lodgiq.com
Shubham Vishwakarma
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