Senior Data Scientist
Wipro
- Location
- Dallas, USA-TX, USA, 18612<br/>
- Work model
- On-Site
- Level
- Senior
- H-1B history
- 906 approvals (FY2023)
- Posted
- 1d ago
Skills
About this role
Job Description
Start applying with LinkedIn
Start
Please wait...
Job Title
Senior Data Scientist
City
Dallas
State/Province
Texas
Posting Start Date
8/10/26
Wipro Limited (NYSE: WIT, BSE: 507685, NSE: WIPRO) is a leading technology services and consulting company focused on building innovative solutions that address clients’ most complex digital transformation needs. Leveraging our holistic portfolio of capabilities in consulting, design, engineering, and operations, we help clients realize their boldest ambitions and build future-ready, sustainable businesses. With over 230,000 employees and business partners across 65 countries, we deliver on the promise of helping our customers, colleagues, and communities thrive in an ever-changing world. For additional information, visit us at www.wipro.com.
Job Description
Seeking a Senior Data Scientist with 10+ years of experience and a Master's or PhD in a quantitative field. The ideal candidate will have strong Python expertise, hands-on experience building and deploying machine learning pipelines, and a solid foundation in statistical and ML techniques. Experience with Databricks, SQL, cloud platforms, and large-scale data processing is highly preferred, with airline industry experience being a plus. ͏
Minimum Qualifications – Education & Prior Job Experience Master or PhD degree with 5+ years of experience in quantitative discipline (e.g., Data Science, Machine Learning Engineer, Computer Science, Applied Mathematics, Statistics, etc.) Experience in Operations research is mandatory Python proficiency (production-grade coding, modularization, testing, performance tuning) Hands on experience with building Gen AI applications – prompt engineering, classifiers, knowledge bases, RAG solutions, LLMs as judges, etc. Hands-on experience with ML/AI pipeline development and productionization (model deployment, orchestration, monitoring, and optimization) Depth of knowledge in statistical