• The role involves working with our partners across the organization to help them drive value by through scalable machine learning and data science solutions
• You will be working with a scrum team comprising of data scientists, business analysts, data engineers, and subject matter experts to deliver well-defined projects
• You will be tasked with designing and creating machine learning models and retraining systems
• You will also have to manage a team of junior ML Engineers to ensure they are utilized appropriately and are working on impactful problems
• Often, you will have to lead the steps from taking a prototype built by a data scientist and work with the team to put that model in production
• This will involve making the model scalable and efficient (parallelizing, using appropriate libraries, adding basic efficiencies from the code/data/architecture etc)
• This can also entail building or rewriting the model from scratch
• Creating a model governance architecture for retraining (upon drift) will also be your responsibility
• In addition, creating the architecture/framework for performance evaluation and feedback loop will also be expected, prior to handover to ML Ops team
• Your model deployment will most likely be in the cloud (AWS), and we ll look for the appropriate experience at your end
• Any experience with dataiku is a plus
• Some reporting and visualization skills will come in handy too
• You don t have to be an expert in any of these topics but need to be able to demonstrate aptitude and some experience
• Experience with healthcare data (specifically, RWE data and claims, EHR) is a plus
• Healthcare data is sometimes unstructured and mostly in the form of text and images, so NLP and/or computer vision experience is a desirable
• We will look to your help in creating technical roadmaps for the projects, and in their nimble execution
• We are looking for someone with 4+ years of experience in the data science/engineering space

Required Experience and Skills:

Minimum 4+ years of professional experience in Applied Machine Learning, with at least 2 years on cloud environment (AWS, Azure, GCP).

Experience with AWS Tech Stack (Sagemaker, glue jobs, step functions, airflow, etc.). Experience in model governance monitoring, CI/CD (Jenkins, etc.), pylint. Experience in putting models into production, Building microservices from models (And notebooks), Experience with papermill (Good to have), Comfortable with Command Line, Experienced with Containers and Kubernetes

Self-motivation, proactivity, and ability to work independently with minimum direction.

Excellent business acumen, with proven ability to understand business processes in detail - both at global and region/country levels - and translate these into user stories and detailed business requirements.

Excellent interpersonal and communication skills, along with the ability to communicate appropriately and confidently with colleagues from different backgrounds and seniority levels.

Excellent organizational skills, with ability to navigate a complex matrix environment and organize/prioritize work efficiently and effectively.

Hands-on experience writing production-grade ML code.

Preferred Experience and Skills:

Coding:

Hands on coding experience in Python/R/Scala/Java or any other OOP; ETL using SQL/shell scripting.

Some experience in SageMaker, Databricks, MLflow Spark/distributed compute environment.

Experience using cloud-based SQL noSQL databases (Redshift, BQ, Athena, Mongo, so on).

Any experience with MLOPs tools is also a plus.

Delivery:

Experiences with project management and data analytics project delivery. Ability to communicate with business user/customer and with IT operations. Good overview of complex Data analytics solutions, ability to explain consequences to both IT and business.

Education Minimum Requirements:

BE/B. Tech degree in Science, Engineering, Mathematics or related quantitative field

MS/M. Tech preferred

Key Skills

Claims; Coding; GCP; Project management; Shell scripting; Healthcare; Scrum; Monitoring; SQL; Python

About Company

MSD operates its human health business in India through three separate legal entities: MSD Pharmaceuticals Private Limited, Organon (India) Private Limited, and Fulford (India) Limited. Since its existence in India, the company has moved quickly in laying the foundation for a business that is differentiated by its focus through launching innovative products relevant to India. MSD in India also has presence in Animal Health via MSD Animal Health with its vaccines facility located in Pune, Maharashtra.