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We’re hiring a mid-to-senior Machine Learning Engineer / Data Scientist to build and deploy machine learning solutions that drive measurable business impact. You should be strong in core data science and applied machine learning, comfortable working with real-world data, and capable of turning mod
As a Data Scientist / Data Analyst / Data Science Specialist for Adidev Technologies Inc. Demonstrated experience using machine learning, deep learning, statistical methodology, and simulation/optimization modeling in geospatial, network topography, recommendation-systems, environmental systems and/
Maintain and improve data pipelines in Microsoft Fabric, including Data Pipelines, Dataflows, and Notebooks, to keep data flowing reliably across the business. Our data platform is already built on Microsoft Fabric using a Medallion architecture (Bronze, Silver, Gold), with clean, structured data fl
Provide subject matter expertise in data modeling, ETL architecture, semantic layer design, and analytics lifecycle best practices to shape and transform data from D365 F&O and Azure Data Lake into optimized structures for enterprise analytics. Excels in fast-paced and evolving environments, especia
Developing reports and analytics using data from data warehouse and Salesforce using Excel, SQL, Tableau, and other reporting/analytics tools. Writes clearly and informatively; Edits work for spelling and grammar; Varies writing style to meet needs; Presents numerical data effectively; Able to read
This role collaborates across the business to identify analytic gaps, design scalable data models, and deliver high-impact dashboards and insights. Develop, optimize, and maintain data views, models, and tables using. Experience building data models and transformations using.
You are comfortable working in modern cloud data warehouses with SQL to prepare data for modeling, and can collaborate effectively with data engineers on production pipelines. You have 6+ years of experience in machine learning roles building and shipping statistical or machine learning models into
Prototype and train learning-based models using a data-centric approach, applying techniques such as automated feature engineering, active learning, and fine-tuning on curated datasets; Design, develop, and maintain efficient data and feature extraction pipelines to support ML engineers in accessing