Project Leader

Axtria - Ingenious Insights; Gurugram District; On-site; INR 1,800,000 - 3,000,000; Full time

Job summary

Axtria - Ingenious Insights in India seeks a driven data science professional to tackle complex analytics and support pharma decision making. You will design cloud-based MLOps pipelines, work with Kubeflow, MLFlow, DataRobot and Airflow, and apply advanced AI/ML methods for business challenges.

You will program in Python and other languages, leverage Linux and ML frameworks, and collaborate on automation, data pipelines, and self-service analytics tools.

Qualifications

• 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
• Knowledge of self-service analytics platforms and ML tooling is expected; familiarity with pharma/ Life Sciences is a plus

Responsibilities

• Design and implement cloud solutions and build MLOps pipelines on cloud platforms
• Experience with MLOps frameworks like Kubeflow, MLFlow, DataRobot, Airflow, Docker and Kubernetes
• Programming languages like Python, Go, Ruby or Bash; strong Linux background and ML framework knowledge
• Understand tools used by data scientists and contribute to software development and test automation
• Apply advanced AI/ML algorithms and their business applications
• Develop applications and digital automation solutions, Low Code/No Code platforms, APIs and exposure to DevOps
• Familiarity with Dataiku/ KNIME/ Alteryx; MS Excel knowledge is mandatory; Life Sciences familiarity is a plus

Skills

Python

R

SQL

Excel

Machine Learning

Forecasting

Data Analysis

Pharma Commercial Know How

HEOR EPI and Economic Analysis

HEOR Simulation Analysis

Patient Data Analytics Know How

Dataiku

KNIME

Alteryx

Education

Bachelor of Engineering in Statistics

Tools

Dataiku

KNIME

Alteryx

Docker

Kubernetes

Job description

Job Description:

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

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