Position Summary
To be a driven business analyst who can work on complex Analytical problems and help the customer in better business decision making especially in the area of Pharma (domain).
Job Responsibilities- Ability to design and implement cloud solutions and ability to build MLOps pipelines on cloud solutions (AWS, MS Azure or GCP)
- Experience with MLOps Frameworks like Kubeflow, MLFlow, DataRobot, Airflow etc., experience with Docker and Kubernetes, OpenShift.
- Programming languages like Python, Go, Ruby or Bash, good understanding of Linux, knowledge of frameworks such as scikit-learn, Keras, PyTorch, Tensorflow, etc.
- Ability to understand tools used by data scientist and experience with software development and test automation.
- Good understanding of advanced AI/ML algorithms & their applications
- Applications and Digital Automation Solutions, Low Code /No Code and Automation Platforms, designing API's and exposure to DevOps, React/Angular, containers, building visualization layer.
- Knowledge of self-service analytics platforms such as Dataiku/ KNIME/ Alteryx will be an added advantage. MS Excel knowledge is mandatory. Familiarity with Life Sciences is a plus
Education
Bachelor of Engineering in Statistics
Work Experience
Must have Skills: -
- 3+ years of experience in the data science space – preferably with the end to end automated ecosystem including, but not limited to, building data pipelines, developing & deploying scalable models, orchestration, scheduling, automation, ML operations
Skills that give you an edge: -
- Strong analytical skills to solve and model complex business requirements are a plus. With lifesciences or pharma background.
Behavioural Competencies
Teamwork & Leadership
Motivation to Learn and Grow
Ownership
Cultural Fit
Project Management
Communication
Technical Competencies
Python
R
SQL
EXCEL
MMx
Forecasting
Machine Learning
Pharma Commercial Know How
HEOR EPI and Economic Analysis
HEOR Simulation Analysis
Patient Data Analytics Know How
Dataiku
KNIME
Others
