Data Science Leader
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:
- · Develop analytics practice including consulting management, practice and business development with a strong of broad-based experience in diverse industries
- · Generate and execute the Data Science roadmap strategy for practice
- · Develop internal industry solutions with management for practice
- · Provide guidance on overall practice to ensure successful delivery while balancing internal initiatives.
- · Quickly understand client needs, assemble teams, manage delivery, and articulate findings to client executives.
- · Prospect, generate, and deliver new business opportunities in given sector to meet revenue targets.
- · 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.
- · Mentor and develop team
- · Grow data science practice by meeting business goals through client prospecting, responding to proposals, identifying and closing opportunities within identified client accounts.
- · Participate in client discussions, interact with CxOs at client organization to articulate the value of data science approaches, different service offerings and guide them on implementation of the same.
- · Collaborate with client managers in a broad range of sectors to identify business use cases and develop solutions in driving impact through data science and analytics, communicate results, and inform practice group through reports and presentations.
- · Develop, enhance, and maintain client relations while ensuring client satisfaction.
- · Ability to successfully deliver and manage multiple client engagements globally.
- · 10+ years professional work experience as a data scientist or on advanced analytics / statistics projects
- · Master’s degree or PhD 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.
- · Possess executive presence and ability to drive senior executive thinking
- · Value engineering (distilling a business case)
- · Consulting engagement management / economics
- · Skilled with practice / business development
- · 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.
- · Expertise using PowerPoint and clearly articulating findings/ presenting solutions.
- · Excellent team-oriented interpersonal skills and demonstrated leadership.
- · Track record delivering successful data science projects and managing global teams.
- · Demonstrated leadership by building Data Science teams and fostering growth.
- · Proven success generating growth and hitting revenue targets.
Candidates should be flexible / willing to work across this delivery landscape which includes and not limited to Agile Applications Development, Support and Deployment.
Applicants for employment in the US must have valid work authorization that does not now and/or will not in the future 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.
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.
Click the following link for more information on your rights as an Applicant: http://www.capgemini.com/resources/equal-employment-opportunity-is-the-law