Azure Data Scientist

UNIFY Dots is a global technology and software solutions company specializing in Microsoft Dynamics 365 based solutions. We are seeking an Azure Data Scientist who will be responsible for designing, building, and experimenting with machine learning models using Microsoft Azure.

Your job duties include the following tasks and responsibilities:

• Define business goals and translate them into machine learning problems and success metrics
• Design and implement data models suited for analytical and machine learning workloads
• Perform feature engineering and feature selection based on business context
• Build, train, evaluate, and iterate machine learning models
• Run experiments and track results using Azure Machine Learning
• Use notebooks for data exploration, model development, and validation
• Document assumptions, model behavior, and results for business and technical stakeholders
• Collaborate with data engineers and solution architects to ensure data readiness
• Work closely with business and technology teams to ensure models align with real business outcomes.
• Certified in Microsoft Azure AI Fundamentals (AI-900) and Microsoft Azure Data Fundamentals (DP-900)

• Bachelor’s Degree in Computer Science, Engineering, Information Technology, or related field
• 3–5 years of experience in data science, machine learning, or related roles
• Strong experience with Python for data analysis and machine learning
• Experience with Azure ML Python SDK (v2)
• Hands-on experience with Azure Machine Learning (workspaces, experiments, models)
• Proficiency using Jupyter Notebooks in Azure ML Studio for experimentation and modeling
• Solid understanding of data modeling concepts (features, labels, training data, validation)
• Experience building and comparing regression, classification, or clustering models
• Ability to translate business requirements into machine learning solutions with clear outcomes
• Strong analytical and problem-solving skills
• Good communication skills in English (written and verbal)

Good to Have:

• Exposure to ML lifecycle practices (experimentation, evaluation, deployment readiness)
• Familiarity with common ML libraries (e.g., scikit-learn, pandas, NumPy)
• Experience working in cross-functional teams (business, engineering, analytics)

Benefits 

• Market competitive compensation
• Medical Insurance for Team member + Spouse + Children + Parents
• Laptop for Work from Home while working at Unify Dots
• People before Profit Culture that values team members over financial numbers