Senior Machine Learning Engineer
8 hours ago
At LTIMindtree, we are seeking a skilled Data Scientist with expertise in O9 technology.
Total Experience: 5 to 8 years required
Job Location: Bangalore
We are looking for an individual who can apply a variety of machine learning techniques such as clustering, regression, ensemble learning, neural nets, and time series optimizations to real-world problems.
The ideal candidate will develop and/or optimize models for demand sensing and forecasting optimization using Heuristic LP, GA, anomaly detection, simulation, and stochastic models. Additionally, they will utilize the latest advancements in AI and ML to solve business problems.
The successful candidate will have experience in time series forecasting in scale using heuristic-based hierarchical best-fit models and algorithms like exponential smoothing, ARIMA, Prophet, and custom parameter tuning.
In this role, you will work collaboratively with Clients, Project Management, Solution Architects, Consultants, and Data Engineers to ensure successful delivery of o9 projects.
Required Skills and Qualifications:
- 2+ Years of experience in time series forecasting in scale using heuristic-based hierarchical best-fit models and algorithms like exponential smoothing, ARIMA, Prophet, and custom parameter tuning.
- Experience in applied analytical methods in the field of Supply Chain and Planning like demand planning, supply planning, market intelligence, optimal assortments, pricing, inventory, etc.
- Bachelor's Degree in Computer Science, Mathematics, Statistics, Economics, or related field.
- Languages: Python and/or R for Data Science, SQL.
- Deep Knowledge of statistical and machine learning algorithms, building scalable ML frameworks, identifying and collecting relevant input data, feature engineering, tuning, and testing.
Estimated Salary: ₹1,200,000 - ₹2,400,000 per annum (dependent on experience)
Benefits: We value team spirit and frequent communication is key. If you are interested in this role, please submit your resume.
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