Jobs → Data & Analytics → Data Analytical Specialist / Scientist

About the Role TekStaff IT Solutions is seeking an experienced Data Analytical Specialist / Scientist to develop advanced analytics, predictive models, and AI-driven insights that support strategic business decisions and enterprise-wide initiatives. Key Responsibilities • Design and develop advanced analytics, predictive models, and machine learning solutions • Perform exploratory data analysis to identify patterns, trends, and business opportunities • Translate business challenges into analytical approaches, hypotheses, and measurable outcomes • Assess data quality, availability, and readiness for AI and analytics initiatives • Develop prototypes and proofs of concept to validate analytical solutions • Evaluate and validate model performance using statistical and machine learning techniques • Identify high-value AI opportunities and assess business value and feasibility • Collaborate with Data Engineers, Data Architects, Product Managers, and business stakeholders • Define analytical KPIs and measure business outcomes • Communicate complex analytical findings and recommendations to technical and executive audiences • Apply Responsible AI, privacy, data governance, and model risk principles Requirements • Deep expertise in Statistics, Probability, Predictive Modelling, and Machine Learning • Strong hands-on experience with Classification, Regression, and Clustering • Feature Engineering and Model Selection • Advanced proficiency in Python and SQL • Hands-on experience with machine learning frameworks and real-world enterprise datasets • Strong experience with Azure Machine Learning (ML Studio) and Microsoft Foundry / Azure AI Foundry • Experience building end-to-end ML pipelines covering experimentation, training, evaluation, and operationalization • Familiarity with Databricks, Azure OpenAI, Power BI, Git, VS Code, and Jira • Strong analytical, problem-solving, and stakeholder management skills • Ability to translate analytical insights into measurable business outcomes • Degree in Data Science, Statistics, Mathematics, Computer Science, Economics, Engineering, or a related quantitative discipline, or equivalent experience