An ideal candidate should have:

• Overall experience of 2-5 Years, with experience in the data science / ML space is a must
• Some experience in the following quantitative fields: Deep learning, Reinforcement Learning, Causal Inference, A/B Testing, Multi-armed Bandits, and Design of Experiments
• Demonstrated proficiency in leveraging open source libraries and packages such as Spark, TensorFlow, Keras, PyTorch to solve Enterprise problems
• Deep proficiency in modeling techniques such as content based filtering, collaborative filtering, clustering etc.
• Good to have knowledge in Deep Learning (open source frameworks like Tensorflow, Keras and/or PyTorch) with applications focused on Recommendation Engines (such as feed forward neural networks, convolutional neural networks, or recurrent neural networks)
• Experience working with large, complex data using Hadoop or Spark or any other big data platforms
• Good to have strong knowledge of secondary data sources including syndicated sales, promotional & marketing data, longitudinal patient level data; payer data (IQVIA – XPONENT/DDD/HCOS/LAAD/CLAIMS, SHA / SHS/ Truven Rx, Mx, Dx Claims, MMIT, DRG)
• Proficiency using ML in a variety of contexts, particularly text classification and clustering
• Experience with data visualization tools such as tableau, and/or Qlik is nice to have
• General experience in ML software engineering, especially –
  • proficiency with R or Python a must and experience with PySpark will be an added advantage
  • experience with Git, Gitlab is nice to have
  • understanding of software testing (unit tests, integration tests, smoke tests)
  • good software engineering practices, design patterns
  • bash/shell scripting is nice to have
  • experience with cloud platforms (preferred AWS)
• Demonstrated ability to solve problems and think outside the box.
• Good in time-management, project management, and teamwork; Strong attention to detail
• Experience translating research or analysis to communicate (in presentations and in writing) concise and compelling business stories that influence decisions and strategy