data analyst

data engineer

ai developer

senior ai engineer

ai/ml engineer

ai data scientist

Datamatics Technologies

<div>
 
 Job Title:
 
 AI Data Scientist (Offshore)
 
 
 
 Duration:
 
 6 Months (Extendable)
 
 
 Experience:
 
 &nbsp;6&ndash;8 Years
 
 
 Location:
 
 Offshore (Remote)
 
 
 Industry:
 
 Multi-Industry (with focus on Financial Sector)
 
 
 Employment Type:
 
 Contract (6 Months - Higher possiblity for extension)
 
 
 
 Job Summary
 
 
 We are seeking a highly skilled
 
 AI Data Scientist
 
 with hands-on experience in building and deploying advanced data science and machine learning models, particularly within the
 
 financial services domain
 
 . The ideal candidate will have strong proficiency in
 
 Python, SQL
 
 , and
 
 Google Cloud Platform (GCP)
 
 tools &mdash; leveraging platforms like
 
 BigQuery, Vertex AI, Dataflow, Dataproc, Pub/Sub, GCS, and Looker
 
 to deliver scalable and automated AI solutions.
 
 
 This is an exciting
 
 6-month contract role (with potential extension)
 
 focused on developing
 
 descriptive, predictive, and prescriptive models
 
 and deploying them in production using
 
 MLOps best practices
 
 .
 
 
 
 Key Responsibilities
 
 <ul>
 <li>
 
 Design and develop
 
 data science and machine learning models
 
 across descriptive, predictive, and prescriptive analytics.
 
 </li>
 <li>
 
 Work closely with business stakeholders&mdash;especially in the
 
 financial sector
 
 &mdash;to translate complex problems into AI-driven solutions.
 
 </li>
 <li>
 
 Develop and automate
 
 end-to-end ML pipelines
 
 on
 
 GCP
 
 using Vertex AI, Dataflow, Pub/Sub, and Dataproc.
 
 </li>
 <li>
 
 Implement
 
 MLOps
 
 frameworks for continuous integration, deployment, and monitoring of machine learning models.
 
 </li>
 <li>
 
 Analyze large datasets using
 
 BigQuery
 
 and other GCP-native tools for data transformation, feature engineering, and model training.
 
 </li>
 <li>
 
 Visualize insights and performance metrics using
 
 Looker
 
 and other BI tools.
 
 </li>
 <li>
 
 Collaborate with data engineers, analysts, and cloud architects to ensure seamless model deployment and scalability.
 
 </li>
 <li>
 
 Evaluate model performance and refine algorithms for improved accuracy and business impact.
 
 
 </li>
 </ul>
 
 Required Skills &amp; Qualifications
 
 <ul>
 <li>
 
 
 5&ndash;8 years
 
 of professional experience in
 
 data science, AI/ML
 
 , and analytics roles.
 
 </li>
 <li>
 
 Proven expertise in
 
 Python
 
 (NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch) and
 
 SQL
 
 for data analysis and model development.
 
 </li>
 <li>
 
 Hands-on experience with
 
 GCP ecosystem
 
 , including:
 
 <ul>
 <li>
 
 
 BigQuery
 
 (data querying and transformation)
 
 </li>
 <li>
 
 
 Vertex AI
 
 (model training, tuning, deployment)
 
 </li>
 <li>
 
 
 Dataflow / Dataproc
 
 (data processing pipelines)
 
 </li>
 <li>
 
 
 Pub/Sub
 
 (event-driven data streaming)
 
 </li>
 <li>
 
 
 GCS (Google Cloud Storage)
 
 and
 
 Looker
 
 (visualization and reporting)
 
 </li>
 </ul>
 </li>
 <li>
 
 Strong knowledge of
 
 MLOps automation
 
 and continuous deployment best practices.
 
 </li>
 <li>
 
 Experience developing models in
 
 financial services
 
 (risk scoring, fraud detection, customer analytics, forecasting, etc.).
 
 </li>
 <li>
 
 Strong understanding of
 
 statistical modeling
 
 ,
 
 feature engineering
 
 , and
 
 model performance evaluation
 
 .
 
 </li>
 <li>
 
 Excellent problem-solving and communication skills with ability to work in multi-industry environments.
 
 
 </li>
 </ul>
 
 Preferred Qualifications
 
 <ul>
 <li>
 
 Experience in
 
 multi-cloud
 
 or hybrid environments.
 
 </li>
 <li>
 
 Knowledge of
 
 CI/CD pipelines
 
 for ML (GitHub Actions, Jenkins, or Cloud Build).
 
 </li>
 <li>
 
 Exposure to
 
 deep learning frameworks
 
 (TensorFlow, PyTorch).
 
 </li>
 <li>
 
 Experience in
 
 time-series forecasting
 
 ,
 
 credit modeling
 
 , or
 
 financial risk analytics
 
 .
 
 </li>
 </ul>
</div>

AI Data Scientist

Datamatics Global Services Ltd

<div><h2 class="jobSectionHeader">Job Title: AI Data Scientist (Offshore)</h2>
Duration: 6 Months (Extendable) 
Experience: 6&ndash;8 Years 
Location: Offshore (Remote) 
Industry: Multi-Industry (with focus on Financial Sector) 
Employment Type: Contract (6 Months - Higher possiblity for extension)<h3 class="jobSectionHeader">
Job Summary</h3>
We are seeking a highly skilled AI Data Scientist with hands-on experience in building and deploying advanced data science and machine learning models, particularly within the financial services domain. The ideal candidate will have strong proficiency in Python, SQL, and Google Cloud Platform (GCP) tools &mdash; leveraging platforms like BigQuery, Vertex AI, Dataflow, Dataproc, Pub/Sub, GCS, and Looker to deliver scalable and automated AI solutions.
This is an exciting 6-month contract role (with potential extension) focused on developing descriptive, predictive, and prescriptive models and deploying them in production using MLOps best practices.<h3 class="jobSectionHeader"> 
Key Responsibilities</h3><ul><li>
Design and develop data science and machine learning models across descriptive, predictive, and prescriptive analytics.</li><li>
Work closely with business stakeholders&mdash;especially in the financial sector&mdash;to translate complex problems into AI-driven solutions.</li><li>
Develop and automate end-to-end ML pipelines on GCP using Vertex AI, Dataflow, Pub/Sub, and Dataproc.</li><li>
Implement MLOps frameworks for continuous integration, deployment, and monitoring of machine learning models.</li><li>
Analyze large datasets using BigQuery and other GCP-native tools for data transformation, feature engineering, and model training.</li><li>
Visualize insights and performance metrics using Looker and other BI tools.</li><li>
Collaborate with data engineers, analysts, and cloud architects to ensure seamless model deployment and scalability.</li><li>
Evaluate model performance and refine algorithms for improved accuracy and business impact.</li></ul><h3 class="jobSectionHeader"> 
Required Skills &amp; Qualifications</h3><ul><li>
5&ndash;8 years of professional experience in data science, AI/ML, and analytics roles.</li><li>
Proven expertise in Python (NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch) and SQL for data analysis and model development.</li><li>
Hands-on experience with GCP ecosystem, including:<ul><li>
BigQuery (data querying and transformation)</li><li>
Vertex AI (model training, tuning, deployment)</li><li>
Dataflow / Dataproc (data processing pipelines)</li><li>
Pub/Sub (event-driven data streaming)</li><li>
GCS (Google Cloud Storage) and Looker (visualization and reporting)</li></ul></li><li>
Strong knowledge of MLOps automation and continuous deployment best practices.</li><li>
Experience developing models in financial services (risk scoring, fraud detection, customer analytics, forecasting, etc.).</li><li>
Strong understanding of statistical modeling, feature engineering, and model performance evaluation.</li><li>
Excellent problem-solving and communication skills with ability to work in multi-industry environments.</li></ul><h3 class="jobSectionHeader"> 
Preferred Qualifications</h3><ul><li>
Experience in multi-cloud or hybrid environments.</li><li>
Knowledge of CI/CD pipelines for ML (GitHub Actions, Jenkins, or Cloud Build).</li><li>
Exposure to deep learning frameworks (TensorFlow, PyTorch).</li><li>
Experience in time-series forecasting, credit modeling, or financial risk analytics.</li></ul>
RE2l5yQYY6</div>

<div><h2 class="jobSectionHeader">Job Title: AI Data Scientist (Offshore)</h2>
Duration: 6 Months (Extendable) 
Experience: 6&ndash;8 Years 
Location: Offshore (Remote) 
Industry: Multi-Industry (with focus on Financial Sector) 
Employment Type: Contract (6 Months - Higher possiblity for extension)<h3 class="jobSectionHeader">
Job Summary</h3>
We are seeking a highly skilled AI Data Scientist with hands-on experience in building and deploying advanced data science and machine learning models, particularly within the financial services domain. The ideal candidate will have strong proficiency in Python, SQL, and Google Cloud Platform (GCP) tools &mdash; leveraging platforms like BigQuery, Vertex AI, Dataflow, Dataproc, Pub/Sub, GCS, and Looker to deliver scalable and automated AI solutions.
This is an exciting 6-month contract role (with potential extension) focused on developing descriptive, predictive, and prescriptive models and deploying them in production using MLOps best practices.<h3 class="jobSectionHeader"> 
Key Responsibilities</h3><ul><li>
Design and develop data science and machine learning models across descriptive, predictive, and prescriptive analytics.</li><li>
Work closely with business stakeholders&mdash;especially in the financial sector&mdash;to translate complex problems into AI-driven solutions.</li><li>
Develop and automate end-to-end ML pipelines on GCP using Vertex AI, Dataflow, Pub/Sub, and Dataproc.</li><li>
Implement MLOps frameworks for continuous integration, deployment, and monitoring of machine learning models.</li><li>
Analyze large datasets using BigQuery and other GCP-native tools for data transformation, feature engineering, and model training.</li><li>
Visualize insights and performance metrics using Looker and other BI tools.</li><li>
Collaborate with data engineers, analysts, and cloud architects to ensure seamless model deployment and scalability.</li><li>
Evaluate model performance and refine algorithms for improved accuracy and business impact.</li></ul><h3 class="jobSectionHeader"> 
Required Skills &amp; Qualifications</h3><ul><li>
5&ndash;8 years of professional experience in data science, AI/ML, and analytics roles.</li><li>
Proven expertise in Python (NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch) and SQL for data analysis and model development.</li><li>
Hands-on experience with GCP ecosystem, including:<ul><li>
BigQuery (data querying and transformation)</li><li>
Vertex AI (model training, tuning, deployment)</li><li>
Dataflow / Dataproc (data processing pipelines)</li><li>
Pub/Sub (event-driven data streaming)</li><li>
GCS (Google Cloud Storage) and Looker (visualization and reporting)</li></ul></li><li>
Strong knowledge of MLOps automation and continuous deployment best practices.</li><li>
Experience developing models in financial services (risk scoring, fraud detection, customer analytics, forecasting, etc.).</li><li>
Strong understanding of statistical modeling, feature engineering, and model performance evaluation.</li><li>
Excellent problem-solving and communication skills with ability to work in multi-industry environments.</li></ul><h3 class="jobSectionHeader"> 
Preferred Qualifications</h3><ul><li>
Experience in multi-cloud or hybrid environments.</li><li>
Knowledge of CI/CD pipelines for ML (GitHub Actions, Jenkins, or Cloud Build).</li><li>
Exposure to deep learning frameworks (TensorFlow, PyTorch).</li><li>
Experience in time-series forecasting, credit modeling, or financial risk analytics.</li></ul>
i6GpPhb9iD</div>

<div><h2 class="jobSectionHeader">Job Title: AI Data Scientist (Offshore)</h2>
Duration: 6 Months (Extendable) 
Experience: 6&ndash;8 Years 
Location: Offshore (Remote) 
Industry: Multi-Industry (with focus on Financial Sector) 
Employment Type: Contract (6 Months - Higher possiblity for extension)<h3 class="jobSectionHeader">
Job Summary</h3>
We are seeking a highly skilled AI Data Scientist with hands-on experience in building and deploying advanced data science and machine learning models, particularly within the financial services domain. The ideal candidate will have strong proficiency in Python, SQL, and Google Cloud Platform (GCP) tools &mdash; leveraging platforms like BigQuery, Vertex AI, Dataflow, Dataproc, Pub/Sub, GCS, and Looker to deliver scalable and automated AI solutions.
This is an exciting 6-month contract role (with potential extension) focused on developing descriptive, predictive, and prescriptive models and deploying them in production using MLOps best practices.<h3 class="jobSectionHeader"> 
Key Responsibilities</h3><ul><li>
Design and develop data science and machine learning models across descriptive, predictive, and prescriptive analytics.</li><li>
Work closely with business stakeholders&mdash;especially in the financial sector&mdash;to translate complex problems into AI-driven solutions.</li><li>
Develop and automate end-to-end ML pipelines on GCP using Vertex AI, Dataflow, Pub/Sub, and Dataproc.</li><li>
Implement MLOps frameworks for continuous integration, deployment, and monitoring of machine learning models.</li><li>
Analyze large datasets using BigQuery and other GCP-native tools for data transformation, feature engineering, and model training.</li><li>
Visualize insights and performance metrics using Looker and other BI tools.</li><li>
Collaborate with data engineers, analysts, and cloud architects to ensure seamless model deployment and scalability.</li><li>
Evaluate model performance and refine algorithms for improved accuracy and business impact.</li></ul><h3 class="jobSectionHeader"> 
Required Skills &amp; Qualifications</h3><ul><li>
5&ndash;8 years of professional experience in data science, AI/ML, and analytics roles.</li><li>
Proven expertise in Python (NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch) and SQL for data analysis and model development.</li><li>
Hands-on experience with GCP ecosystem, including:<ul><li>
BigQuery (data querying and transformation)</li><li>
Vertex AI (model training, tuning, deployment)</li><li>
Dataflow / Dataproc (data processing pipelines)</li><li>
Pub/Sub (event-driven data streaming)</li><li>
GCS (Google Cloud Storage) and Looker (visualization and reporting)</li></ul></li><li>
Strong knowledge of MLOps automation and continuous deployment best practices.</li><li>
Experience developing models in financial services (risk scoring, fraud detection, customer analytics, forecasting, etc.).</li><li>
Strong understanding of statistical modeling, feature engineering, and model performance evaluation.</li><li>
Excellent problem-solving and communication skills with ability to work in multi-industry environments.</li></ul><h3 class="jobSectionHeader"> 
Preferred Qualifications</h3><ul><li>
Experience in multi-cloud or hybrid environments.</li><li>
Knowledge of CI/CD pipelines for ML (GitHub Actions, Jenkins, or Cloud Build).</li><li>
Exposure to deep learning frameworks (TensorFlow, PyTorch).</li><li>
Experience in time-series forecasting, credit modeling, or financial risk analytics.</li></ul>
olqQlu28No</div>

<div></div><div><div><div><div><ul><div>2 - 3 Years</div>
<div></div><div>1 Opening</div>
 <div>Bangalore, Hyderabad</div></ul></div><div> 
<div><div>
</div></div></div></div><div></div><div><h3 class="jobSectionHeader">Role description</h3>
<div>Role: Data Engineering &amp; AI Specialist We are seeking an experienced Data Engineering and AI Data Science and professional with deep expertise across the full data stack, and cutting-edge Agentic AI systems. Required Technical Expertise: Programming &amp; Scripting Languages: &bull; Advanced proficiency in Python, R, Spark, SQL, PL/SQL, and UNIX Shell Scripting &bull; Strong skills in building AI/ML pipelines and agent-based architectures Data and Datawarehouse technologies &bull; Expert-level experience with Teradata, Greenplum, Oracle 11g, SQL Server, PostgreSQL, Azure Data Lake Storage, and Snowflake &bull; Extensive experience with Informatica PowerCenter, Informatica Intelligent Cloud Services (IICS), StreamSets, and Apache Kafka &bull; Proven expertise in Azure Databricks for large-scale data processing and ML operations &bull; Familiarity with Snowflake cloud data warehouse &bull; Proficient in NumPy, Pandas, Matplotlib, GGplot, Dplyr, Scikit-learn, and Deequ for data analysis, visualization, and quality validation &bull; Experience with deep learning frameworks (TensorFlow, PyTorch) for agent model development &bull; Hands-on experience with Apache Airflow, Informatica Workflow Manager, Control-M, and StreamSets Data Collector &bull; Experience orchestrating multi-step AI agent workflows and autonomous task execution &bull; Strong command of Windows, UNIX, and Linux environments &bull; Proficient with ServiceNow, Team Foundation Server (TFS), CI/CD pipelines, GitHub, Jira, Microsoft SharePoint, Salesforce (SFDC), Power BI, Tableau, SAP, and Qlik Sense &bull; Experience with MLOps tools and agent monitoring platforms &bull; Design and implementation of autonomous AI agents and multi-agent systems &bull; Experience with LLM-based agents, reasoning frameworks, and tool-use patterns &bull; Development of AI agents with planning, memory, and decision-making capabilities &bull; Integration of AI agents with external tools, APIs, and data sources &bull; Prompt engineering and chain-of-thought reasoning for complex task decomposition &bull; Experience with retrieval-augmented generation (RAG) and vector databases &bull; Knowledge of agent orchestration, monitoring, and evaluation frameworks &bull; Master&rsquo;s degree in data science/data engineering or similar fields &bull; 5+ years&rsquo; experience &bull; Proven record on capabilities related Global enterprise applications</div>
<h3 class="jobSectionHeader">Skills</h3>
<div>Python,Pyspark,Etl Tools</div></div></div></div>
 <div><h3 class="jobSectionHeader">About UST</h3>
<div>UST is a global digital transformation solutions provider. For more than 20 years, UST has worked side by side with the world&rsquo;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&rsquo; organizations. With over 30,000 employees in 30 countries, UST builds for boundless impact&mdash;touching billions of lives in the process.</div></div>

Data Engineering ( Python, Pyspark, SQL, Oracle)

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