As the world s leading independent, end-to-end IT services company, DXC Technology (NYSE: DXC) leads digital transformations for clients by modernizing and integrating their mainstream IT, and by deploying digital solutions at scale to produce better business outcomes. The company s technology independence, global talent, and extensive partner network enable 6,000 private and public-sector clients in 70 countries to thrive on change. DXC is a recognized leader in corporate responsibility. For more information, visit www.dxc.technology and explore thrive.dxc.technology, DXC s digital destination for changemakers and innovators.
Role Description : Lead the strategy and implementation for the Data Architecture components of the solution by taking into consideration the client s business case, objectives, requirements, and constraints, utilizing the DXC technology value system as the foundation for solution development. The technical domain of the data architect includes conceptual, logical and physical data modeling, data standards, best practices, tools and technologies, data security and privacy, database architecture, design, development, capacity planning, performance tuning, and administration.
- Research and develop statistical learning and Machine Learning models for data analysis.
- Understanding information needs and extracting data from a variety of sources in order to create analytics deliverables that meet those needs.
- Leverage models to address key growth challenges, cross-channel spend allocation, response modeling, and marketing program attribution.
- Collaborate with Product Management to understand Business needs and devise possible solutions.
- Ideas to generate key decision making KPIs.
- Implement new statistical or other mathematical methodologies as needed for specific models or analysis.
- Optimize joint development efforts through appropriate database use and project design.
- Master s Degree in Computer Science, Statistics, Applied Math or related field.
- 7+ years practical experience with SAS, ETL, Data Processing, Database Programming and Data Analytics
- Excellent understanding of Machine Learning and Artificial Intelligence Techniques and Algorithms.
- Experience with common data science tools like (but not limited to) R, Weka, NumPy, MatLab, etc.
- Good knowledge of statistics.
- Experience with programming languages such as Java and Python.
- Skilled in Reporting and Data Visualization Software, with strong presentation skills.
- Experience with SQL (Structured Query language) programming.
- Extensive background in data mining and statistical analysis
- Ability to understand various data structures and common methods in data transformation
- Excellent pattern recognition and predictive modeling skills.
- NoSQL and BigData experience preferred.