While technology is the heart of our business, a global and diverse culture is the heart of our success. We love our people and we take pride in catering them to a culture built on transparency, diversity, integrity, learning and growth.
If working in an environment that encourages you to innovate and excel, not just in professional but personal life, interests you- you would enjoy your career with Quantiphi!
Machine Learning Engineer with 4–6 years of experience, specializing in time-series forecasting. He/she will lead data preparation and profiling efforts to design, build, and deploy predictive models for demand planning and forecasting. Experience in the retail domain is a strong plus. This role requires readiness to travel to our client office in Bengaluru twice a week.
Must have Skills:
4–6 years of hands-on experience in Machine Learning / Data Science.
Strong expertise in time-series forecasting and handling sequential data.
Build, evaluate, and tune statistical and ML-based forecasting models (ARIMA, LightGBM, Prophet, LSTMs/Transformers).
Solid experience in data preparation, data quality assessment, and exploratory data analysis (EDA) on raw, large-scale datasets.
Advanced proficiency in Python and SQL.
Proven ability to work independently as a solo team member with minimal supervision, taking end-to-end ownership of tasks from data preparation to model development and deployment.
Ability to speak to customer confidently to present his/her own work not only in pure technical terms but also from a functional or business perspective.
Experience with AWS Cloud Platform and services
Sagemaker ***
Hands-on experience with ML frameworks (pandas, scikit-learn, PyTorch/TensorFlow, statsmodels, Prophet) and MLOps tools (Docker, Airflow, MLflow).
Good to have skills:
Prior experience in Retail / E-Commerce (e.g., demand planning, SKU-level forecasting, stockout prediction).
Computer Vision Experience: Exposure to basic computer vision tasks, image preprocessing, and classification using tools like OpenCV, PIL, or CNN frameworks (e.g., handling visual data, planograms, or shelf-monitoring images in retail).
Other:
If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!
