Data Scientist

Data Scientist (Azure)

Duration:

Location:

About Us

Data Analytics, IT Optimization, Cloud, and Virtualization

smarter, more efficient, and cost-effective IT ecosystems

About the Role

Data Scientist with strong Azure expertise

building and deploying predictive models for financial forecasting or financial services

Key Responsibilities

• Use

  Azure Data Factory (ADF)

  ,

  Azure Synapse Analytics

  , and related Azure services for financial data integration, transformation, and analysis.
• Apply

  statistical modeling

  ,

  machine learning

  , and

  AI frameworks

  (PyTorch, TensorFlow, Scikit-learn, etc.) to solve complex business and financial problems.
• Build and refine

  predictive models

  for

  financial forecasting

  ,

  risk analysis

  , and

  revenue optimization

  , ensuring accuracy and business impact.
• Develop, deploy, and scale

  machine learning models

  and

  data pipelines

  within the Azure ecosystem.
• Collaborate with business stakeholders to translate

  financial objectives

  into actionable

  data-driven insights

  .
• Optimize data workflows for

  efficiency, scalability, and accuracy

  .
• Partner with infrastructure and cloud teams to ensure

  secure, robust, and cost-optimized deployments

  .
• Document, monitor, and enhance models in production to maintain long-term accuracy and performance.

Qualifications

Required:

• Proven experience as a

  Data Scientist

  using

  Azure cloud services

  (ADF, Synapse, Azure Machine Learning, Databricks preferred).
• Hands-on experience building

  financial forecasting

  ,

  risk

  , or

  predictive models

  (e.g., revenue, demand, churn, credit risk).
• Proficiency in

  Python

  for data manipulation, analysis, and model development.
• Experience with

  machine learning frameworks

  (PyTorch, TensorFlow, or similar).
• Strong understanding of

  data warehousing

  ,

  ETL processes

  , and

  big data analytics

  .
• Excellent problem-solving ability with skill in

  translating business and financial goals into technical solutions

  .

Preferred:

• Background in the

  financial services industry

  (banking, insurance, fintech, or investment management).
• Experience in

  data center optimization

  ,

  IT infrastructure analytics

  , or

  cloud/virtualization

  environments.
• Familiarity with

  ITIL practices

  and

  process improvement methodologies

  .
• Strong communication skills with the ability to work effectively with both technical and non-technical teams.