Deputy Manager - Data Sciences

WNS Global Services · via Himalayas ·

TypeFull-time job
LocationIndia
Posted2 hours ago
Experience: Knowledge of Consumer Healthcare and Pharmaceutical Business Research would be an added advantage
Min. Qualification required to man the position: Bachelor's, Master's in Computer Science, or MCA degree, Data Science, AI/ML, IT, or related fields
Min. Experience required to man the position:4-5 years
Key Responsibility Indicators
Data and AI Specialist, Consulting role
Key Responsibilities:

Python developer experienced with Azure Cloud using Azure Data bricks for

Data Science: Create models and algorithms to analyze data and solve business problems

Application Architecture: Knowledge of enterprise application integration and application design

Cloud Management: Knowledge of hosting and supporting applications of Azure Cloud

Data Engineering: Build and maintain systems to process and store data efficiently

Collaboration: Work with different teams to understand their needs and provide data solutions. Share insights through reports and presentations

Research: Keep up with the latest tech trends and improve existing models and systems

KEY INTERACTIONS (iNTERNAL/EXTERNAL CUSTOMERS)

Internal

External
Team Members
Client Stakeholders
COMPETENCIES & SKILL SET

Must have:

Python development in AI / ML and Data Analysis:
Strong programming skills in Python or R, SQL

Proficiency in statistical analysis and machine learning techniques

Hands on experience in NLP and NLU

Experience with data visualization and reporting tools (e.g., Power BI)

Experience with Microsoft Power Platforms and SharePoint, including (e.g., Power Automate)

Data Engineering:
Expertise in designing and maintaining data pipelines and ETL processes

Experience with data storage solutions (e.g. Azure SQL)

Understanding of data quality and governance principles

Experience with Databricks for big data processing and analytics

Cloud Management:
Proficiency in cloud platforms (e.g., Azure)

Knowledge of hosting and supporting applications of Azure Cloud

Knowledge of cloud security and compliance best practices

Collaboration and Communication:
Experience in agile methodologies and project management tools (e.g., Jira)

Ability to translate complex technical concepts into business terms

Experience working in cross-functional teams

Excellent English communication skills, both written and verbal

Research and Development:
Ability to stay updated with the latest advancements in data science, AI/ML, and cloud technologies

Experience in conducting research and improving model performance

Must exhibit following core behaviors:
Taking ownership / accountability of the projects assigned

Flexibility to work on cross-team projects across all domains

Critical thinking

Self-motivated, able to work autonomously

Qualification:

B Tech / M Tech /MCA, master’s in computer, Data Science, AI/ML, IT, or related fields

4-5 years of relevant experience

Proficiency in Python, R, cloud platforms (Azure), and data visualization tools like Power BI

Advanced certifications and experience with big data technologies, real-time data processing
Azure Data Scientist Associate

Azure Data Engineer Associate

Excellent English communication skills
WNS, part of Capgemini, is an Agentic AI-powered leader in intelligent operations and transformation, serving more than 700 clients across 10 industries, including Banking and Financial Services, Healthcare, Insurance, Shipping and Logistics, and Travel and Hospitality. We bring together deep domain excellence – WNS’ core differentiator – with AI-powered platforms and analytics to help businesses innovate, scale, adapt and build resilience in a world defined by disruption.Our purpose is clear: to enable lasting business value by designing intelligent, human-led solutions that deliver sustainable outcomes and a differentiated impact. With three global headquarters across four continents, operations in 13 countries, 65 delivery centers and more than 66,000 employees, WNS combines scale, expertise and execution to create meaningful, measurable impact.
Originally posted on Himalayas
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