We are looking for a Data Scientist with 2–4 years of hands-on experience to lead and drive data-driven initiatives across Smart Node’s ecosystem. In this role, you will not only build advanced statistical and machine learning models, but also lead end-to-end development, mentor junior engineers, and productionize scalable data products.
You will work closely with cross-functional business units including Sales, Operations, Supply Chain, and Customer Experience, as well as firmware, cloud, and hardware teams to transform raw IoT telemetry, ERP workflows, and user interactions into scalable, production-grade intelligence.
Key Responsibilities
Technical Leadership and Team Guidance
Lead data projects by acting as the technical point of contact for data science initiatives, owning solutions from problem formulation to production deployment.
Ensure code quality by reviewing work, promoting modular coding standards, designing robust system architectures, and mentoring junior data scientists and analysts.
Collaborate with cross-functional teams and business leaders across Sales, HR, Finance, and Operations to translate business goals into technical roadmaps.
End-to-End Machine Learning and AI Solutions
Design and implement demand and inventory optimization models using time-series forecasting to streamline inventory and reduce stockouts.
Develop sales intelligence solutions including lead scoring and churn prediction models to improve conversion rates and customer lifetime value.
Build predictive maintenance models using IoT telemetry data such as device logs and streaming data in collaboration with hardware and cloud teams.
Design and deploy NLP and Generative AI systems including automated support tools and text classification solutions using modern frameworks.
Productionization, MLOps and Architecture
Deploy machine learning models into production using scalable microservices built with FastAPI or Flask, ensuring monitoring for performance and model drift.
Work with data and cloud engineers to build and maintain robust ETL pipelines integrating mobile applications, cloud systems, and ERP data.
Oversee the development of real-time dashboards to track hardware health, operational efficiency, and key business metrics.
Required Skills
Core Data Science and Engineering
2–4 years of experience building, deploying, and maintaining production-level machine learning models.
Strong proficiency in Python including object-oriented programming, design patterns, and libraries such as Pandas, NumPy, Scikit-learn, XGBoost, and LightGBM.
Experience in building and deploying REST APIs using FastAPI, Flask, or Django with Docker.
Advanced SQL skills including data modeling, complex queries, and handling large datasets.
Machine Learning and AI
Hands-on experience with deep learning frameworks such as PyTorch or TensorFlow.
Experience with NLP workflows, transformer models, and integrating Generative AI APIs or vector databases into production systems.
Basic understanding of computer vision pipelines using tools such as OpenCV or related frameworks.
MLOps and Production Tools
Familiarity with model tracking, versioning, and deployment tools such as MLflow, DVC, Git, and Docker.
Good to Have
Experience with Edge AI or embedded systems using tools like TensorFlow Lite or ONNX.
Knowledge of IoT protocols and streaming systems such as MQTT, Kafka, or WebSockets.
Experience with voice AI systems such as speech-to-text or virtual assistants.
Familiarity with workflow orchestration tools like Airflow, Prefect, or Dagster.
Experience working with cloud platforms such as AWS, GCP, or Azure.
Ability to build dashboards using tools like Power BI, Tableau, or Apache Superset.
Pay: ₹250,000.00 - ₹600,000.00 per year
Benefits:
- Flexible schedule
- Health insurance
- Leave encashment
- Life insurance
- Paid time off
- Provident Fund
Location:
- Vadodara, Gujarat (Required)
Work Location: In person
