This role is for one of the Weekday's clients

Min Experience: 2 years

Location: India

JobType: full-time

We are looking for forward-thinking and driven professionals to join us on an exciting journey to transform healthcare through AI. As a member of our team, you’ll collaborate with leading healthcare providers, leveraging AI-powered Remote Patient Monitoring (RPM) solutions to address critical industry challenges — from enhancing operational efficiency to improving patient outcomes and shaping future care delivery models.

Requirements

Key Responsibilities:

• Design, develop, and optimize machine learning algorithms to address complex healthcare challenges.
• Leverage healthcare datasets to generate meaningful insights and contribute to academic case studies and publications.
• Collaborate with product and marketing teams to extract actionable feedback and support ongoing optimization.
• Enhance and upgrade existing data pipelines and machine learning workflows for improved performance and scalability.
• Ensure solutions meet business requirements in terms of reliability, accuracy, and speed.
• Stay current with advancements in AI/ML technologies and ensure the software stack reflects industry best practices.

Required Qualifications:

• Minimum of 5 years of experience in data science or a related role.
• Strong foundation in statistics and machine learning principles.
• Proficient in scripting and programming languages, preferably Python (Julia or R also considered).
• Experience working with time-series data and large-scale datasets.
• Hands-on experience with deep learning frameworks such as TensorFlow, Keras, or PyTorch.
• Familiarity with big data tools such as Spark or Hadoop and the ability to contribute to pipeline development.
• Strong analytical and design skills, with a critical mindset and the ability to evaluate and improve current systems.
• Excellent data storytelling and communication skills.

Skills:

Python, TensorFlow/Keras/PyTorch, Time-Series Analysis, Spark/Hadoop, Statistical Modeling, Data Pipeline Optimization