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, on 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.
- Assist with the mentorship and development of consultants.
- Assist in growing data science practice by meeting business goals through client prospecting, responding to proposals, identifying and closing opportunities within identified client accounts.
- 3-5 years 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.
- PhD preferred.
- 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, ect.).
- Knowledge of or experience working with database systems (e.g. SQL, NoSQL, MongoDB, Postgres, ect.)
- Experience working with big data distributed programming languages, and ecosystems (e.g. S3, EC2, Hadoop/MapReduce, Pig, Hive, Spark, SAP HANA ect.)
- 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-scrapping.
- Experience building and deploying predictive models.
- Experience with PowerPoint and ability to clearly articulate findings and present solutions.
- Excellent team-oriented and interpersonal skills.
Applicants for employment in the US must have valid work authorization that does not now require sponsorship of a visa for employment authorization in the US by Capgemini.
With more than 190,000 people, Capgemini is present in over 40 countries and celebrates its 50th Anniversary year in 2017. A global leader in consulting, technology and outsourcing services, the Group reported 2016 global revenues of EUR 12.5 billion (about $13.8 billion USD at 2016 average rate). Together with its clients, Capgemini creates and delivers business, technology and digital 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 Rightshore, its worldwide delivery model.
Learn more about us at www.capgemini.com.
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.
Click the following link for more information on your rights as an Applicant: http://www.capgemini.com/resources/equal-employment-opportunity-is-the-lawApply now