Data Scientist IV

Team: Data Science

Location: Bangalore, Karnataka

Commitment: Full Time Employee

Workplace Type: onsite

What you will do

• Own and deliver solutions across multiple charters by formulating well-scoped problem statements and driving them to execution with measurable impact
• Mentor a team of data scientists (DS2s and DS3s), helping them with project planning, execution, and on-call issue resolution
• Design and optimize key user journeys (e.g., Reseller Experience, Search, Fraud Systems) by identifying user intents and behavioral patterns from large-scale data
• Collaborate with machine learning engineers and big data teams to build scalable ML pipelines and improve inference performance
• Continuously track and improve model performance using state-of-the-art (SOTA) techniques and libraries
• Lead experimental design for usability improvements and user growth, leveraging statistical rigor
• Contribute to system-level thinking by enhancing internal tools, frameworks, and libraries to improve team efficiency and code quality
• Partner with engineering to ensure data reliability, compliance with security/PII guidelines, and integration of models into production systems
• Proactively explore new areas of opportunity through research, data mining, and academic collaboration, including publishing and attending top-tier conferences
• Communicate findings, plans, and results clearly with DS, product, and tech stakeholders, and create technical documentation consumable by both DS and engineering teams
• Conduct research collaborations with premier colleges and universities Attend conferences and publish research papers

What you will need

• A Bachelor's degree in Computer Science, Data Science, or a related field; a Master’s is a plus
• 6–8 years of experience in data science with a strong track record of building and deploying ML solutions at scale
• Deep understanding of core ML techniques — supervised, unsupervised, and semi-supervised learning — along with strong foundations in statistics and linear algebra
• Exposure to deep learning concepts and architectures (e.g., CNNs, RNNs, Transformers) and their practical applications
• Proficiency in Python and SQL, with experience in building data pipelines and analytical workflows
• Hands-on experience with large-scale data processing using Apache Spark, Hadoop/Hive, or cloud platforms such as GCP
• Strong programming fundamentals and experience writing clean, maintainable, and production-ready code
• Excellent analytical and problem-solving skills — the ability to extract actionable insights from messy and high-volume data
• Solid grasp of statistical testing, hypothesis validation, and common pitfalls in experimental design
• Experience designing and interpreting A/B tests, including uplift measurement and segmentation
• Ability to work closely with product and engineering teams to translate business goals into scalable ML or data solutions


Bonus points for:
• Experience with reinforcement learning or sequence modeling techniques
• Contributions to ML libraries, internal tools, or research publications