Data Scientist

New Relic is a leader in Observability industry and has been on the forefront of developing cutting edge AI/ML solutions. We are seeking an experienced and dynamic Data Scientist to join our team. You will develop ML solutions for customer problems from scratch utilizing large complex data sets of both structured and unstructured formats. Your responsibilities will include developing, prototyping and productionizing ML models. You will have broad expertise in ML techniques including Conventional ML (both supervised and unsupervised), Deep Learning and GenAI/LLMs. With a start-up growth story, these are exciting times for New Relic to make a significant impact on AI Observability and even more exciting for Data Scientist to join us and contribute to that journey.

• Conduct multiple experiments using different ML techniques for defined objectives of regression/classification/clustering tasks.
• Develop prototypes for end-to-end ML solutions from pre-processing to the model evaluation stages.
• Perform basic and advanced data analysis to uncover trends and correlations in the data. Utilize statistical methods to drive insightful
• recommendations for process improvements.
• Be abreast of the advanced research and techniques in the ML and Deep-learning space to adopt latest techniques for experimentation and
• prototype-building.
• Design and analyze A/B tests with appropriate statistical methods
• Communicate data-driven recommendations internally in the team and externally

• 2+ years proven experience as a Data Scientist, or in a similar role.
• Master's degree in Machine Learning, Statistics, Mathematics, Computer Science, or related quantitative field.
• Strong proficiency in scripting language, Python.
• Proficiency in data querying languages (SQL) and data visualization tools (Tableau/Looker/PowerBI).
• Proficiency in Machine Learning techniques - both ML Breadth and Depth.
• Proficiency in ML model development process including but not limited to Feature Selection, Feature Engineering, Pre-processing and Post-processing, Hyperparameter tuning.
• Familiarity with common ML/NLP libraries such as PyTorch, Tensorflow, HuggingFace Transformers, and SpaCy.
• Familiarity with AWS/Azure/GCP tech stack (AWS Sagemaker, Redshift, S3, EC2, Glue etc.)
• Good technical communication skills, ability to work independently and priortize parallel tasks well.
• Ability to translate business needs into data science / analytical initiatives.

• Experience developing OR - Optimization models like inventory and network optimization, have hands on experience in Linear Programming.
• Experience in Observability domain is a bonus.
• Experience in Reinforcement Learning models.
• Experience of deploying and managing ML models in production environments is a plus.