17 hours ago
Mumbai, India or Bengaluru, IndiaSenior
Responsibilities
- Lead data preparation, profiling, data quality assessment, and exploratory analysis on large-scale raw datasets.
- Build, evaluate, tune, and deploy statistical and machine-learning forecasting models for demand planning and forecasting.
- Own tasks end to end from data preparation through model development and deployment with minimal supervision.
- Collaborate with business stakeholders to understand requirements and present work to customers in technical and business terms.
- Use AWS Cloud Platform and SageMaker for machine-learning workflows.
- Apply machine-learning frameworks and MLOps tools including pandas, scikit-learn, PyTorch or TensorFlow, statsmodels, Prophet, Docker, Airflow, and MLflow.
Requirements
- 4–6 years of hands-on experience in machine learning or data science.
- Strong expertise in time-series forecasting and sequential data.
- Advanced proficiency in Python and SQL.
- Experience with AWS Cloud Platform and services, including SageMaker.
- Hands-on experience with pandas, scikit-learn, PyTorch or TensorFlow, statsmodels, Prophet, Docker, Airflow, and MLflow.
- Ability to work independently, take end-to-end ownership, and communicate confidently with customers in technical and business terms.
- Retail or e-commerce experience is strongly preferred, particularly demand planning, SKU-level forecasting, or stockout prediction.
- Basic computer vision experience with image preprocessing and classification using OpenCV, PIL, or CNN frameworks is preferred.
- Good verbal and written communication skills in English.
Benefits
- Travel to the client office in Bengaluru twice a week is required.
- The company describes a culture focused on transparency, diversity, integrity, learning, growth, innovation, and personal and professional development.
Categories
About Quantiphi
Quantiphi is an AI-first digital engineering and consulting firm that designs and implements machine learning, data, and cloud solutions for large enterprises across industries. Its teams build production systems—such as generative AI applications, computer vision, and predictive analytics—primarily on Google Cloud and other hyperscalers, delivered as professional services and managed solutions. Founded in 2013 and headquartered in Marlborough, Massachusetts, the company is privately held and a Google Cloud partner.