Position Summary

We are looking for a skilled Data Analyst with expertise in NumPy and PyTorch to join our

Advanced Analytics team in Bengaluru. The role will involve working with high-dimensional

healthcare datasets to extract insights, build predictive models, and automate decisionmaking pipelines that directly impact Cardinal Health’s operations and clinical decisionmaking.

Key Responsibilities

• Extract, clean, manipulate, and analyze complex structured and unstructured

healthcare data using Python libraries such as NumPy, pandas, and PyTorch.

• Develop deep learning and machine learning models using PyTorch for applications

like demand forecasting, patient behavior modeling, and logistics optimization.

• Work collaboratively with data scientists, business analysts, clinicians, and software

engineers to build scalable analytics solutions.

• Design, evaluate, and interpret statistical analyses and data science experiments.

• Build end-to-end data pipelines and predictive dashboards integrated into business

systems or external-facing tools.

• Implement and fine-tune algorithms for classification, regression, clustering, and time

series forecasting using PyTorch and NumPy.

• Assist in deploying models into production using containerized environments

(Docker/Kubernetes preferred) and MLOps pipelines.

• Document model assumptions, processes, and validation methods for both technical

and non-technical stakeholders.

Required Qualifications

• Bachelor’s or Master’s degree in Computer Science, Mathematics, Statistics, Data

• Science, Engineering, or related quantitative fields.

• Minimum 0-3 years of hands-on experience in data analytics or applied machine learning.

• Proficiency in Python with advanced knowledge of NumPy for numerical data processing.

• Practical experience with PyTorch for deep learning model building and experimentation.

• Strong understanding of data structures, algorithms, and object-oriented programming.

• Experience in data cleaning, data wrangling, and handling large datasets.

• Familiarity with pandas, SciPy, Matplotlib, and scikit-learn.

• Ability to communicate complex technical concepts clearly to cross-functional teams.

• Experience with Jupyter Notebooks, version control (Git), and APIs.

Preferred Qualifications

• Experience working in healthcare, clinical analytics, or pharmaceutical data

environments.

• Exposure to cloud platforms like AWS, Azure, or GCP for model training and data

storage.

• Working knowledge of SQL, Power BI, or Tableau.

• Experience with model deployment tools like MLflow, FastAPI, or TensorRT.

• Familiarity with HIPAA, HL7, or other healthcare data compliance standards.

What You’ll Gain

• A chance to work on impactful projects in the healthcare ecosystem that improve

patient outcomes.

• Access to state-of-the-art infrastructure for machine learning, cloud computing, and big

data analytics.

• Collaboration with global experts across healthcare technology, data science, and

operations.

• Competitive compensation package with performance bonuses.

• Career development support, certifications, and continuous learning programs.