Consultant – Data Science

Skill: Consultant - Data Science

Exp: 4 to 7 years

Location: Hyderabad

Shift: Night Shift

As a Consultant, you contribute to technical delivery across modernization and cloud transformation projects. You work under the guidance of senior consultants and architects, applying strong hands-on skills to implement solutions that align with established standards. You build subject-matter expertise while strengthening delivery consistency and technical execution.

Responsibilities

· Execute delivery tasks that support solution architectures and modernization priorities.

· Implement application, data, or cloud components based on established technical designs.

· Collaborate with team members across App Innovation, Cloud Platform, and Data & AI to ensure integrated delivery.

· Follow delivery frameworks, coding standards, and quality checks established for the project.

· Participate in design walkthroughs and apply feedback to improve technical execution.

· Collaborate with architects, project managers, and client stakeholders to drive successful outcomes.

· Support junior team members by sharing knowledge and best practices.

· Support documentation, testing, and validation activities aligned to delivery needs.

· Provide status updates, surface risks, and collaborate with leads to maintain execution quality.

· Apply current Azure technologies and Microsoft frameworks to optimize solutions for maintainability, performance, and cost efficiency.

· Contribute to reusable assets and internal frameworks as assigned.

· Manage workload and commitments to meet utilization goals while maintaining architectural quality across engagements.

· Invests in internal thought leadership, culture of feedback, knowledge-sharing, and/or Intellectual Property development opportunities, including communities of practice and internal initiatives.

· Delivery and Consulting Excellence

· Build trust with managers and product owners, influencing priorities and roadmaps in ways that support the client’s long-term interests.

· Support effective Agile practices by ensuring a clear Definition of Done, and data-informed course corrections based on telemetry and feedback.

· Demonstrated ability to leverage AI and emerging technologies to improve productivity, enhance decision-making, streamline delivery processes, and drive measurable business value. Commitment to continuous learning and adoption of new digital capabilities is required.

Requirements

· 2 or more years of relevant experience implementing technical solutions on Azure.

· Two years of experience in data science, machine learning, or advanced analytics, preferably in consulting or client-facing settings.

· Demonstrated ability to build and deploy data and ML components on Azure or comparable cloud environments.

· Proficiency in one or two of the following areas:

o Data Engineering & Integration - Spark, Azure Data Factory, Synapse, Delta Lake, or Data Lake Storage.

o Machine Learning - model development, feature engineering, validation, and tuning using Python (pandas, NumPy, scikit-learn, PySpark).

o MLOps & Automation - MLflow, Azure ML pipelines, CI/CD concepts, or model monitoring.

o Analytics & Visualization - Power BI, Plotly, Seaborn, Matplotlib for communicating insights.

o Cloud & AI Foundations - exposure to Azure Databricks, Fabric, or Prompt Flow; basic understanding of agentic frameworks (Semantic Kernel, AutoGen).

· Familiarity with data modeling, experiment design, and statistical inference concepts.

· Knowledge of modern development tools such as GitHub, Copilot, and version control workflows.

· Exposure to data governance, metadata management, or Responsible AI practices.

· Prior hands-on work with Databricks Unity Catalog or Microsoft Fabric.

· Relevant Azure or Databricks certifications in Data, AI, or Architecture.

· Technical foundation in one Azure domain (Application Innovation, Cloud Platform, or Data & AI)

· Demonstrated ability to execute assigned tasks within application, cloud, or data domains.

· Experience working within delivery teams and following established technical processes with attention to detail.

· Effective communicator able to work collaboratively across project teams.

· Exposure to hybrid or multi-cloud environments is a plus