028773 - Data Scientist - Manager
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 junior staff.
- Assist in growing 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.
- Work with Capgemini’s global data science leadership to execute identified business use cases on time and manage project delivery / client expectations.
- Develop, enhance, and maintain client relations while ensuring client satisfaction.
- Ability to successfully deliver and manage multiple client engagements globally.
- 5-10 years professional work experience as a data scientist or on advanced analytics / statistics projects.
- Preferred sector focus with 3+ years’ experience in one of the following 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.
- 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.
- Expertise using PowerPoint and clearly articulating findings/ presenting solutions.
- Excellent team-oriented interpersonal skills and demonstrated leadership.
- Proven track record delivering successful data science projects and working with global teams.
- Demonstrated leadership by building Data Science teams and fostering growth.
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.
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.
Click the following link for more information on your rights as an Applicant: http://www.capgemini.com/resources/equal-employment-opportunity-is-the-law