Data Science Engineer

Hello,

We are looking for a person who can work with us and contribute in the development of critical infrastructure and functionality.
Please see the Job description and responsibilities below and share your Resume with us to understand the fitment at imember@peoplelc.com. Before that, please sign up and apply at our platform www.peoplelc.com

About PeopleLC
PeopleLC is a forward-thinking global enterprise dedicated to building the future of AI-driven technology, individual career acceleration, hyper-specialised healthcare, and corporate growth strategy. We pride ourselves on cultivating a world-class working culture that treats every employee as a long-term partner. We offer market-leading, best-in-the-industry compensation packages, cutting-edge technical freedom, and a clear path toward long-term career growth.

1. Data Science Engineer

Experience Required: 5–8 years
Location: Hybrid / Remote Option Available
Compensation: Best in the industry
Job Summary:
We are seeking an experienced Data Science Engineer to lead the design and implementation of predictive models, route optimization algorithms, and advanced analytical features within our software ecosystem. You will bridge the gap between heavy statistics and production-grade engineering.
Core Responsibilities:
Design, build, and deploy production-grade machine learning models and predictive analytics infrastructure.
Handle large-scale data gathering, engineering, pipeline construction, and advanced data cleaning processes.
Conduct extensive time-series forecasting, cluster analysis, and custom route or process optimization modeling.
Collaborate closely with software and data engineering teams to deploy models directly into scalable enterprise systems.
Requirements & Qualifications:
Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, or a relevant quantitative field.
5+ years of verified professional experience in advanced data science or ML engineering environments.
Elite coding capabilities in Python or R alongside expert-level production SQL query design.
Documented experience deploying scalable models using AWS, GCP, Azure, Docker, or Kubernetes.