Data Scientist

Employment Type:Full-time
Education: Not specified
Experience: 2–4 years of hands-on experience in Data Science, Machine Learning, and production ML systems
Location: Vadodara Gujarat- Onsite
About Smart Node:
Smart Node is one of India’s leading brands in wireless home automation, transforming homes, offices, and hotels into smart spaces. With over 8 years of innovation, we are on a mission to simplify lives through cutting-edge automation technology made in India.
Join our passionate and fast-growing team to be part of the next big revolution in smart living.
About the Role:
We're 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.
You'll own data science solutions end-to-end — from problem formulation and statistical analysis to machine learning model development, deployment, monitoring, and productionization. You'll work closely with Sales, Operations, Supply Chain, Customer Experience, firmware, cloud, and hardware teams to transform raw IoT telemetry, ERP workflows, and user interactions into scalable, production-grade intelligence.
The role also involves mentoring junior data scientists/analysts, maintaining code quality, designing robust architectures, and working directly with business leaders to translate business goals into technical solutions.
Key Responsibilities:
Technical Leadership & Team Guidance
· Own data science projects from problem formulation through production deployment
· Act as the technical point of contact for data science initiatives
· Review code, promote modular coding standards, and design robust system architectures
· Mentor junior data scientists and analysts
· Collaborate with Sales, HR, Finance, Operations, and other business teams to translate business requirements into technical roadmaps
Machine Learning & AI Solutions
· Build time-series predictive demand models for demand and inventory optimization
· Develop lead scoring and churn prediction models to improve sales conversion and customer lifetime value
· Build failure forecasting and predictive maintenance models using streaming IoT device data such as heartbeat logs and MQTT payloads
· Design and integrate production-grade LLM applications for automated support and operational text classification
· Work with firmware, cloud, and hardware teams to develop intelligence from IoT telemetry and device data
Productionization, MLOps & Architecture
· Deploy machine learning models into production using scalable microservices such as FastAPI and Flask
· Implement monitoring for model performance, drift, latency, and reliability
· Work with cloud and data engineering teams to build and maintain ETL pipelines
· Integrate data from mobile applications, cloud infrastructure, ERP databases, and IoT systems
· Support the development of high-throughput real-time dashboards for hardware health, operational bottlenecks, and enterprise KPIs
· Follow production-grade coding, deployment, version control, and documentation practices
Who Can Apply (Ideal Backgrounds):
· 2–4 years of hands-on experience building, deploying, and maintaining production ML models
· Strong production-level Python skills with knowledge of OOP, design patterns, and profiling
· Strong command of Pandas, NumPy, Scikit-learn, XGBoost, and LightGBM
· Strong experience developing REST APIs using FastAPI, Flask, or Django
· Good understanding of Docker and microservices architecture
· Advanced SQL skills including data modelling, window functions, and handling structured and unstructured datasets
· Practical experience with PyTorch or TensorFlow
· Hands-on experience with NLP workflows and Hugging Face Transformers
· Experience integrating Generative AI APIs and vector databases into production applications
· Practical understanding of Computer Vision pipelines using technologies such as OpenCV, YOLO, or ResNet
· Familiarity with MLOps practices and tools such as MLflow, DVC, Git, and Docker
Preferred / Good-to-Have Skills:
· Edge AI deployment using TensorFlow Lite or ONNX Runtime
· Experience with IoT protocols and streaming technologies such as MQTT, WebSockets, Kafka, or Kinesis
· Experience with stream processing for real-time IoT data
· Experience developing or integrating voice AI systems, including Speech-to-Text, Whisper, Alexa, or Google Assistant
· Experience with workflow and pipeline orchestration tools such as Airflow, Prefect, or Dagster
· Experience deploying ML models on AWS, GCP, or Azure
· Experience with AWS services such as EC2, S3, SageMaker, or Lambda
· Hands-on experience with BI tools such as Power BI, Tableau, or Apache Superset
Why Join Us?
· Be part of a fast-growing, innovation-driven smart automation company
· Work on real-world AI, ML, IoT, and data-driven products
· Opportunity to build production-grade ML solutions across Sales, Operations, Supply Chain, Customer Experience, and IoT
· Work closely with firmware, cloud, hardware, and business teams
· Opportunity to take technical ownership and mentor junior team members
· Exposure to large-scale IoT telemetry, ERP, mobile application, and enterprise data
· Opportunity to contribute to the next generation of smart home technology

Work arrangement
No