About Capgemini<?xml:namespace prefix = o ns = “urn:schemas-microsoft-com:office:office” />
With more than 170,000 people in over 40 countries, Capgemini is one of the world’s foremost providers of consulting, technology and outsourcing services. The Group reported 2014 global revenues of EUR 10.5 billion. Together with its clients, Capgemini creates and delivers business and technology solutions that fit their needs and drive the results they want. A deeply multicultural organization, Capgemini has developed its own way of working, the Collaborative Business ExperienceTM, and draws on Rightshore®, its worldwide delivery model.
Learn more about us at http://www.capgemini.com/ .
Rightshore ® is a trademark belonging to Capgemini
Capgemini is an Equal Opportunity Employer encouraging diversity in the workplace. All qualified applicants will receive consideration for employment without regard to race, national origin, gender identity/expression, age, religion, disability, sexual orientation, genetics, veteran status, marital status or any other characteristic protected by law.
Sr. Data Analytics
Job Description :
10+ years of relevant years of experience
Ability to interface with business team / traders to understand the requirements and conceptualize & explain analytical solutions
Ability to design and develop detailed use cases
Ability to design algorithms
Work/guide the analyst/developers in designing and reviewing the solutions
Strong presentation and communication skills
Develop data analytics on a big data platform
Perform analytics on huge data volumes on various business domains like (but not limited to) – AML, Trading, Payments, Risk etc.
Understand business requirements and identify analytics techniques, perform data preparation & profiling using statistical methods , design & develop appropriate models (exploratory, computational and quantitative analytics)
Performance testing of the models
Documentations and reporting of the models and their results
Java Map reduce programming
Python or Pig scripting
Advanced Hive QL programming including (but not limited to) table functions, partitioned table function, windowing, npath analysis etc.) that Hive provides along with basic Hive sql.
Knowledge of machine learning algorithms is a strong plus (some examples):
Reinforcement Learning algorithms – e.g. HMMs, MDPs, Kalman filters
Unsupervised learning algorithms towards ‘pattern / relationship hunting’ – e.g. K-means clustering, Hierarchical clustering, PCA
Range of Classification algorithms – e.g. KNN, SVMs, Logistic Regression
Catch all – support for being able to mathematically determine ‘equilibrium-zones’, ‘clusters’ and ‘deviations’ / ‘exceptions’ in data via various machine-learning approaches
Location: NYC, NYApply now