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Senior Machine Learning Engineer - Traditional

Quantiphi15 дн. назад

Коротко

Develops predictive models for sales forecasting and growth prediction using time-series and tabular data; works in Jupyter Notebooks on AWS with S3 and · Needs: 4+ years in traditional ML and predictive modeling; strong Python with Scikit-learn, Pandas, NumPy; AWS S3 and Redshift experience.

Описание от работодателя

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! JOB ROLE - ML Engineer As an ML Engineer This role focuses on predictive modeling development utilizing Jupyter Notebook environments alongside AWS cloud infrastructure services. Must have Skills: Must be capable of working independently with minimal supervision alongside the client's business/technical team 4+ years experience in Traditional Machine Learning & Predictive Modeling: Hands-on experience building and fine-tuning ML models for regression/classification tasks, specifically sales forecasting or growth prediction using time-series and tabular data Python & ML Libraries: Strong command of Python with libraries such as Scikit-learn, Pandas, NumPy, and Jupyter Notebooks for model development and output presentation. Model Testing and evaluation Feature Engineering & EDA AWS Data Ecosystem: Working knowledge of AWS S3 and Amazon Redshift for data ingestion, storage, and retrieval in a cloud development environment Data Preparation & Quality: Experience in data handling, missing values, duplicates, inconsistencies, and building unified analytical datasets from multiple sources Good to have skills: Store/Retail Domain Knowledge: Understanding of retail KPIs, store segmentation frameworks, and business cockpit/reporting concepts Stakeholder Communication: Ability to present model outputs, performance metrics, and insights to non-technical business stakeholders during weekly review cadences If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us !