Manager of Data Science with deep marketing experience. Ability to lead a DS team for client. Ability to help client to define their DS organization. Experience in retail and customer churn is essential. ML is a plus, Excellent client facing skills. Ability to drive a program and expand brand/footprint at client. Knowledge of one to one marketing and churn analytics for retail.
5-10(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, 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.
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.
This is a general description of the Duties, Responsibilities and Qualifications required for this position.
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.
As part of the Capgemini Technology Services Group, this person will be responsible for the full systems lifecycle from requirements gathering through implementation of data analysis solutions.
This person will work closely with our clients and must demonstrate professional knowledge to ensure that the work products and deliverables are of the highest caliber to ensure client satisfaction.
This person will also apply subject matter expertise to identify, develop, and implement techniques to improve engagement productivity, increase efficiencies, mitigate risks, resolve issues, and optimize cost savings and efficiencies for each client.
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