Time since we first saw it
Day 19
Similar jobs usually come down between day 7 and day 57.
At Cognizant, jobs usually come down by about day 21.
From 10,789 similar postings that came down, and 395 of Cognizant’s. Coming down is not always a hire.
Hyderabad, Telangana, India
Live, first seen by us 19 days agoWork setup in the employer’s posting: hybrid remoteFrom the employer’s posting
Employment type in the employer’s posting: Full-timeFrom the employer’s posting
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.
· 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.
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.
· 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:
· 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 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 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.
· 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)
· 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.
· 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.
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).
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 19
Similar jobs usually come down between day 7 and day 57.
At Cognizant, jobs usually come down by about day 21.
From 10,789 similar postings that came down, and 395 of Cognizant’s. Coming down is not always a hire.
139 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Check the employer’s posting for the current role and application details.
Already applied? Track this application
New Data Scientist postings at the employers we follow are down 5% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under Data Scientist, by the work the posting describes.
Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.
Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.
Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.
Skill: Consultant – Data Science
Exp: 4 to 7 years
Location: Hyderabad
Shift: Flexible to work in Shifts
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
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Hyderabad, Telangana, India
· Effective communicator able to work collaboratively across project teams. · Exposure to hybrid or multi-cloud environments is a plus
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We couldn’t identify enough role detail in this saved description to support an AI answer. Read the full posting