With more than 180,000 people in over 40 countries, Capgemini is one of the world's foremost providers of consulting, technology and outsourcing services. The Group reported 2015 global revenues of EUR 11.9 billion. Together with its clients, Capgemini creates and delivers business and technology solutions that fit their needs , enabling them to achieve innovation and competitiveness. A deeply multicultural organization, Capgemini has developed its own way of working,
the Collaborative Business ExperienceTM
, and draws on
, its worldwide delivery model.
Learn more about us at www.capgemini.com
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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.
This is a general description of the Duties, Responsibilities and Qualifications required for this position. Physical, mental, sensory or environmental demands may be referenced in an attempt to communicate the manner in which this position traditionally is performed. Whenever necessary to provide individuals with disabilities an equal employment opportunity, Capgemini will consider reasonable accommodations that might involve varying job requirements and/or changing the way this job is performed, provided that such accommodations do not pose an undue hardship.
Capgemini's robust Outsourcing offerings include: Applications Management, Infrastructure Management and Business Process Management. We combine these services with our deep industry knowledge and experience to provide the change agent to accelerate business growth. We generate quality and speed through our proven tools, methods and global centers. These capabilities, coupled with our program management expertise are tailored to fit the most challenging business needs.
With their expertise in a specific technology environment, Applications Consultants are responsible for software-specific design and realization, as well as testing, deployment and release management, or technical and functional application management of client-specific package based solutions (e.g. SAP, ORACLE). These roles also require functional and methodological capabilities in testing and training.
You focus on building solutions and on maintaining, optimizing and improving a client’s applications and systems. You contribute to a business and technical blueprint and customize the respective Software Package Core Module. You may also be responsible for unit testing, contribute to integration testing, and/or be responsible for the design and delivery of end-user training.
Certification: Has or seeking SE Level 1.
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The Data Science & Analytics practice group at Capgemini is expanding its footprint…rapidly.
As part of the fastest growing digital practice within Capgemini, we work with the latest advanced analytics, machine learning, and big data technologies to extract meaning and value from data in a number of different industries ranging from Media & Entertainment to Life Sciences and everywhere in-between.
Our team has worked with geospatial data, performed social media sentiment analysis, built recommendation systems, created image classification algorithms, solved large-scale optimization problems, and harnessed the massive influx of data generated by the IoT.
The Data Science & Analytics group is the fastest growing digital practice at Capgemini demanding agile innovation.
As part of the Data Science & Analytics group, you will work in a collaborative environment with internal and client resources to understand key business goals, build solutions, and present findings to client executives while solving real-world problems. If you are passionate about solving problems in the realm of cognitive computing, big data, and machine learning while utilizing business acumen, statistical understanding, and technical know-how, the Data Science & Analytics practice group at Capgemini is the best place to grow your career.
Role & Responsibilities:
- Work in collaborative environment with global teams to drive client engagements in a broad range of industries:
Aerospace & Defense, Automotive, Banking, Consumer Products & Retail, Financial Services, Healthcare, High Tech, Industrial Products, Insurance, Life Sciences, Manufacturing, Public Sector, Telecom, Media & Entertainment, and Energy & Utilities.
- Quickly understand client needs, develop solutions, and articulate findings to client executives.
- Provide data-driven recommendations to clients by clearly articulating complex technical concepts through generation and delivery of presentations.
- Analyze and model both structured and unstructured data from a number of distributed client and publicly available sources.
- Perform EDA and feature engineering to both inform the development of statistical models and generate improve model performance and flexibility.
- Design and build scalable machine learning models to meet the needs of given client engagement.
- 0-2 year(s) professional work experience as a data scientist or on advanced analytics / statistics projects.
- Master’s degree from top tier college/university in Computer Science, Statistics, Economics, Physics, Engineering, Mathematics, or other closely related field.
- Strong understanding and application of statistical methods and skills: distributions, experimental design, variance analysis, A/B testing, and regression.
- Statistical emphasis on data mining techniques, Bayesian Networks Inference, CHAID, CART, association rule, linear and non-linear regression, hierarchical mixed models/multi-level modeling, and ability to answer questions about underlying algorithms and processes.
- Experience with both Bayesian and frequentist methodologies.
- Mastery of statistical software, scripting languages, and packages (e.g. R, Matlab, SAS, Python, Pearl, Scikit-learn, Caffe, SAP Predictive Analytics, KXEN, etc.).
- Knowledge of or experience working with database systems (e.g. SQL, NoSQL, MongoDB, Postgres, etc.)
- Experience working with big data distributed programming languages, and ecosystems (e.g. S3, EC2, Hadoop/MapReduce, Pig, Hive, Spark, SAP HANA, etc.)
- Expertise in machine learning algorithms and experience using the following ML techniques: Logistic Regression, Decision Trees, Random Forests, Gradient Boosting, SVMs, Time Series, KMeans, Clustering, NMF).
Preferred experience with NLP, Graph Theory, Neural Networks (RNNs/CNNs), sentiment analysis, and Azure ML.
- Experience building scalable data pipelines and with data engineering/ feature engineering.
Preferred experience with web-scraping.
- Experience building and deploying predictive models.
- Experience with PowerPoint and ability to clearly articulate findings and present solutions.
- Excellent team-oriented and interpersonal skills.
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