Job Description: Azure AI Specialist

Position Title: Data Scientist

Experience Level: 510 years

About the Role

We are seeking a highly skilled Data Scientist with strong hands?on experience across Azure AI and data services to design, build, and operationalize end?to?end machine learning and generative AI solutions. The ideal candidate possesses a solid background in statistical modelling, machine learning engineering, and modern AI frameworks, combined with proven experience productionizing models on Microsoft Azure.

This role will work closely with data engineers, solution architects, product owners, and business stakeholders to deliver scalable and impactful AI-driven products.

Key Responsibilities

AI & Machine Learning

Develop, train, evaluate, and deploy ML and AI models using Azure Machine Learning (Azure ML).
Build and optimize pipelines for training, inference, and continuous integration/continuous deployment (CI/CD) in Azure ML & GitHub/Azure DevOps.
Apply advanced analytics, predictive modelling, NLP, computer vision, and generative AI techniques to solve business problems.
Design responsible AI approaches including monitoring, drift detection, explainability, and governance.
Hands-on approach and be the analytics technical expert who uses large data sets and strong in applying varieties of machine learning methodology / algorithms & Generative / Cognitive AI (e.g. deep learning, NLP, image recognition, text recognition, chatbots, robotics etc) with different data tools in developing the models, running simulations & optimization etc that will drive tangible business outcome.
Being a data science consultant for the business stakeholders and a coach for the team members to recommend and deliver the creative analytics solutions for continuous improvements and solving business questions.
Collaborate with potential partner(s) / vendor(s) or internal teams to develop an efficient prototype, conduct assessment of the AI solution, give feedback, determine areas of improvement, and finalize the design, to automate or streamline operations within the Company.
Implement and manage a high standard of procedural documentation.
Research and experiment with creative and advanced machine learning techniques and tools through POC
Perform regular AI/ ML model monitoring and reporting , monthly or quarterly model refresh, minor update and test that can be done internally (without any dependencies on external team)
Ensure AI Model comply to AI governance practice, including continuous evaluation of model accuracy, performance, and data drift.

Azure AI & Cloud Engineering

Implement solutions using Azure AI services including:
Azure Machine Learning
Azure OpenAI
Azure Cognitive Services (Vision, Language, Speech, Search)
Azure Cognitive Search
Azure Databricks / Spark
Azure Data Factory / Synapse
Azure Event Hub / Service Bus (nice to have)
Optimize model performance, cost management, and cloud resource utilization.
Work with Data engineer on Server upgrade and patches, Infra, end user, security related initiative require support from portfolio. Security and vulnerabilities fix, incident investigation and fixes

Data Science & Analytics

Perform exploratory data analysis (EDA), feature engineering, and data quality assessments.
Present insights and model outputs through clear visualization and storytelling.
Collaborate with business teams to translate requirements into data-driven solutions.

Operationalization & MLOps

Implement machine learning lifecycle best practices, including experiment tracking, model registry, reproducibility, monitoring, and drift management.
Set high ethical standards while applying machine learning models & AI solutions.
Deploy models to real-time endpoints, batch scoring, and edge environments (when applicable).

Required Qualifications

Bachelor's or Master's in Computer Science, Data Science, Mathematics, Engineering, or related field.
510 years of professional experience in Data Science, AI Engineering, or ML Engineering.
Strong practical experience with Azure Machine Learning, Azure OpenAI, and Azure Cognitive Services.
Proficiency in Python, including popular ML libraries.
Hands-on experience with Azure-based ML pipelines, feature stores, data preparation workflows, and model deployments.
Solid understanding of data engineering concepts (Spark, Delta Lake, SQL, data modeling).
Strong foundation in statistics, machine learning algorithms, and evaluation methodologies.

Preferred Qualifications

Experience with Azure Databricks and distributed ML training.
Experience with vector databases, RAG architecture, or production LLM implementations.
Familiarity with MLOps tools: MLflow, GitHub Actions, Azure DevOps, Kubernetes/AKS.
Knowledge in responsible AI, model governance, and ethical AI frameworks.
Industry certifications (e.g., Microsoft Azure Data Scientist Associate, Azure AI Engineer).

Soft Skills

Strong analytical and problem?solving ability.
Able to communicate technical concepts to both technical and non?technical audiences.
Experience working in agile, cross-functional teams.
Proactive, curious, and committed to continuous learning.

Solutions Architect, AI & Data

Data Scientist (Azure AI Specialist)

Senior Solution Architect (Presales – Data & AI)