Job Description

3 - 5 Years
2 Openings
Chennai, Kochi, Trivandrum

Role description

Role Proficiency:



Independently interprets data and analyses results using statistical techniques



Outcomes:



Independently Mine and acquire data from primary and secondary sources and reorganize the data in a format that can be easily read by either a machine or a person; generating insights and helping clients make better decisions.

Develop reports and analysis that effectively communicate trends patterns and predictions using relevant data.

Utilizes historical data sets and planned changes to business models and forecast business trends

Working alongside teams within the business or the management team to establish business needs.

Creates visualizations including dashboards flowcharts and graphs to relay business concepts through visuals to colleagues and other relevant stakeholders.

Set FAST goals


Measures of Outcomes:



Schedule adherence to tasks

Quality - Errors in data interpretation and Modelling

Number of business processes changed due to vital analysis.

Number of insights generated for business decisions

Number of stakeholder appreciations/escalations

Number of customer appreciations

No: of mandatory trainings completed


Outputs Expected:



Data Mining:



Acquiring data from various sources



Reorganizing/Filtering data:



Consider only relevant data from the mined data and convert it into a format which is consistent and analysable.



Analysis:



Use statistical methods to analyse data and generate useful results.



Create Data Models:



Use data to create models that depict trends in the customer base and the consumer population as a whole



Create Reports:



Create reports depicting the trends and behaviours from the analysed data



Document:



Create documentation for own work as well as perform peer review of documentation of others' work



Manage knowledge:



Consume and contribute to project related documents
share point

libraries and client universities




Status Reporting:



Report status of tasks assigned

Comply with project related reporting standards and process



Code:



Create efficient and reusable code. Follows coding best practices.



Code Versioning:



Organize and manage the changes and revisions to code. Use a version control tool like git
bitbucket

etc.




Quality:



Provide quality assurance of imported data
working with quality assurance analyst if necessary.




Performance Management:



Set FAST Goals and seek feedback from supervisor


Skill Examples:



Analytical Skills: Ability to work with large amounts of data: facts figures and number crunching.

Communication Skills: Ability to present findings or translate the data into an understandable document

Critical Thinking: Ability to look at the numbers trends and data; coming up with new conclusions based on the findings.

Attention to Detail: Making sure to be vigilant in the analysis to come with accurate conclusions.

Quantitative skills - knowledge of statistical methods and data analysis software

Presentation Skills - reports and oral presentations to senior colleagues

Mathematical skills to estimate numerical data.

Work in a team environment

Proactively ask for and offer help


Knowledge Examples:



Knowledge Examples



Proficient in mathematics and calculations.

Spreadsheet tools such as Microsoft Excel or Google Sheets

Advanced knowledge of Tableau or PowerBI

SQL

Python

DBMS

Operating Systems and software platforms

Knowledge about customer domain and also sub domain where problem is solved

Code version control e.g. git bitbucket etc


Additional Comments:



About the Role We are looking for a skilled and forward-thinking Cloud AI/ML Engineer to design, develop, and support scalable, secure, and high-performance generative AI applications on AWS. This role will work at the intersection of cloud engineering and artificial intelligence, enabling efficient delivery of state-of-the-art AI capabilities using services like Amazon Bedrock and SageMaker. You'll be part of a collaborative team working on cutting-edge generative AI projects, and you'll play a key role in implementing cloud-native solutions with best practices in infrastructure automation, security, and observability. Key Responsibilities o AI/ML Integration o Leverage Amazon Bedrock for foundation models and SageMaker for custom model training and deployment. o Build and maintain generative AI applications that use AWS-native AI/ML services efficiently. o Deployment & Operations o Develop robust CI/CD pipelines for automating infrastructure deployment and AI model lifecycle management. o Implement real-time monitoring and logging using Amazon CloudWatch and other observability tools. o Ensure availability and reliability of AI systems in production environments. o Security & Compliance o Apply AWS IAM, encryption, and other best practices to protect data and models. o Ensure compliance with organizational and industry-specific data protection standards. o Collaboration & Support o Work closely with data scientists, machine learning engineers, and product owners to translate requirements into robust solutions. o Troubleshoot and resolve issues related to model performance, infrastructure, and AWS services. o Optimization & Documentation o Continuously evaluate and optimize model performance and cloud infrastructure for cost and efficiency. o Document infrastructure, deployment workflows, and best practices for team use and knowledge sharing. o Mentorship & Guidance o Share knowledge of AWS services and generative AI best practices with peers and junior engineers. Required Skills & Experience o Proficiency in AWS services, especially EC2, SageMaker, Bedrock, and IAM. o Strong programming skills in Python and experience with containerization using Docker. o Familiarity with Kubernetes for container orchestration. o Experience building and maintaining CI/CD pipelines for AI applications and MLOps o Strong understanding of data security, compliance, and monitoring tools in AWS. o Hands-on experience managing databases and data flows in cloud environments. Preferred Qualifications o AWS certifications (e.g., AWS Certified Machine Learning - Specialty, AWS DevOps Engineer). o Experience with responsible AI practices for generative models. o Exposure to cost optimization and resource scaling strategies in production AI workloads.

Skills

Aws,Python,Ai

About UST

UST is a global digital transformation solutions provider. For more than 20 years, UST has worked side by side with the world's best companies to make a real impact through transformation. Powered by technology, inspired by people and led by purpose, UST partners with their clients from design to operation. With deep domain expertise and a future-proof philosophy, UST embeds innovation and agility into their clients' organizations. With over 30,000 employees in 30 countries, UST builds for boundless impact--touching billions of lives in the process.