Zoomcar
Data Scientist
- Compensation
- Not disclosed
- Location
- Bangalore
- Work setup
- Hybrid
- Seniority
- Senior
- Employment
- Not specified
- Experience
- 5+ years
- Category
- Data science
- Posted
Skills
Must have
- 5+ years of hands-on experience in data science, ML engineering, or applied AI.
- Strong Python skills: pandas, NumPy, scikit-learn, TensorFlow or PyTorch.
- Solid understanding of Transformer architecture and fine-tuning (LoRA, etc. )
- Strong SQL and large-scale data manipulation experience.
- Solid statistics foundation: hypothesis testing, data distributions, modelling.
- Experience with cloud platforms (AWS/GCP/Azure).
- Experience deploying models via FastAPI/Flask for production use.
- Familiarity with data viz tools (Tableau, Power BI, or Plotly).
Nice to have
- Docker, MLflow, Kubernetes, or Vertex AI experience.
- Big data tools (Spark, Hadoop).
- MLOps / model monitoring exposure.
- Research/publication background.
Full description
We're hiring a Senior Data Scientist / ML Engineer to join our Data Science / AI and ML team in Bengaluru (4 days WFO, Friday WFH). You'll work on predictive models, recommendation systems, and production-grade GenAI applications, including prompt engineering, LLM evaluation, and multimodal deployment for high-accuracy, low-latency outputs. This is a hands-on, end-to-end role: from experimentation through to deploying scalable APIs in production.
Responsibilities:
- Solve complex business problems using large, messy datasets and advanced analytical methods.
- Design, build, and deploy predictive models, recommendation systems, and GenAI-powered features.
- Own prompt engineering and LLM evaluation for production-ready GenAI applications.
- Deploy multimodal solutions optimised for accuracy and latency.
- Build low-failure, low-latency production APIs using FastAPI/Flask.
- Run A/B tests and experiments to validate product/process changes.
- Partner closely with product managers and engineers to translate requirements into insights and shipped features.
Requirements:
- 5+ years of hands-on experience in data science, ML engineering, or applied AI.
- Strong Python skills: pandas, NumPy, scikit-learn, TensorFlow or PyTorch.
- Solid understanding of Transformer architecture and fine-tuning (LoRA, etc. )
- Strong SQL and large-scale data manipulation experience.
- Solid statistics foundation: hypothesis testing, data distributions, modelling.
- Experience with cloud platforms (AWS/GCP/Azure).
- Experience deploying models via FastAPI/Flask for production use.
- Familiarity with data viz tools (Tableau, Power BI, or Plotly).
Nice to have:
- Docker, MLflow, Kubernetes, or Vertex AI experience.
- Big data tools (Spark, Hadoop).
- MLOps / model monitoring exposure.
- Research/publication background.