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:
Collaborate with multiple Business stakeholders and understand their business requirements
Good verbal and written communication in English
If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!
Skills Required
- 4–6 years of hands-on experience in machine learning or data science
- Strong expertise in time-series forecasting and sequential data
- Experience building, evaluating, and tuning statistical and machine-learning forecasting models
- Experience with ARIMA, LightGBM, Prophet, LSTMs, or Transformers
- Experience with data preparation, data quality assessment, and exploratory data analysis on large-scale raw datasets
- Advanced proficiency in Python and SQL
- Ability to work independently with minimal supervision and own tasks end to end from data preparation through deployment
- Ability to confidently present technical work to customers from technical and business perspectives
- Experience with AWS Cloud Platform and services
- Experience with Amazon SageMaker
- Hands-on experience with pandas, scikit-learn, PyTorch or TensorFlow, statsmodels, and Prophet
- Experience with Docker, Airflow, and MLflow
- Prior retail or e-commerce experience, including demand planning, SKU forecasting, or stockout prediction
- Basic computer vision experience, including image preprocessing and classification using OpenCV, PIL, or CNN frameworks
- Ability to collaborate with business stakeholders and understand requirements
- Good verbal and written English communication skills
Quantiphi Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Quantiphi and has not been reviewed or approved by Quantiphi.
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Wellbeing & Lifestyle Benefits — Wellbeing initiatives such as monthly meeting-free AMA-Zen Days, health check-ups, and wellness counseling are designed to reduce burnout and support day-to-day balance. Broader wellness programs reinforce both physical and mental health.
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Flexible Benefits — Remote/hybrid options with flexible working hours provide meaningful autonomy over where and when work gets done. Flexible leave constructs, including sabbaticals and special day leaves, add practical adaptability to the package.
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Parental & Family Support — Paid parental leave in the U.S., alongside maternity and childcare support, signals solid backing for families. These family-oriented policies integrate with a wider health and wellness focus.
Quantiphi Insights
What We Do
Quantiphi is an award-winning AI-first digital engineering company driven by the desire to solve transformational problems at the heart of business. Quantiphi solves the toughest and complex business problems by combining deep industry experience, disciplined cloud, and data-engineering practices, and cutting-edge artificial intelligence research to achieve quantifiable business impact at unprecedented speed.
