Responsibilities

We are looking for ML scientists with a strong background in machine learning to build industry-leading solutions.

• You will work with huge volumes of data to solve real-world ML problems that are productionized into our MLOps platform to be consumed by downstream applications OR become product feature OR stand-alone products.
• Y ou will work with global teams with an opportunity to create phenomenal impact.
• You will combine data sciences depth, programming expertise and mathematical understanding of techniques to deliver state-of-the-art ML solutions for problem solving across the enterprise.
• You will demonstrate a product mindset and look to deliver re-usable components that can be deployed as or into ML services/productized solutions.
• You will partner closely with engineering, product management, analytics & transformation teams from across MCDS to deliver outstanding value to stakeholders and our products.
• We are looking to strengthen our ML footprint across Digital namely e-commerce/direct ( BizApps Direct business around PowerApps & Dynamics Platform), Developer Relations, Learning Portal, Marketplace.
• Prior experience in organizations driving e-commerce ML solutions like recommender system design, User Insight Engine Development, Personalization Engines, Digital Buyer Journey, next Best Action, Marketing Channel Optimization is highly desired.
• Knowledge of client-side scripted web-analytics tools like Adobe (across the suite) is highly valuable.

Qualifications

• Masters degree in Computer Science, Mathematics, Statistics, Physics or related field with 6+ Years of industry experience. Focus on ML preferred. Ph.D. desirable
• Strong expertise in Python programming and one of the Deep Learning frameworks ( PyTorch , MXNet, TensorFlow, Keras )
• Knowledge of (with deep expertise in at-least three of) Classification, Prediction, Recommender Systems, Time Series Forecasting, Anomaly Detection, Optimization, Graph ML, NLP  
•  Hands-on develop ML models using the above techniques across Customer, Partner, Field & Sales in varied domains
  Ability to both use existing libraries (ML, Deep Learning, Re- inforcement Learning) as well as design algorithms ground-up
• Able to prepare data pipelines and feature engineering pipelines to build robust models using SQL, PySpark , Azure Data Studio etc
• Strong research record preferred demonstrated, through publications
  Scientific thinking and ability to invent: Prior experience creating intellectual property through patents desirable.
• Proficient in Relational Databases (SQL) and Big Data Technologies (Hive, PySpark)
• Exposure to real-world MLOps
• Knowledge of working in cloud-computing environment like Azure or AWS or Google Cloud. Azure preferred