-Big data consultant
-Data Science and analytics consultant with proven skills
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.
o 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.
o 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).
o 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.
o 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.
Delivery Architects assess a project’s technical feasibility, as well as implementation risks. They are responsible for designing and implementing a project’s technical architecture. They define the structure of a system, its interfaces, and the principles that guide its organization, software design and implementation. The scope of the Delivery Architect’s role is bounded by the business issue at hand. A Delivery Architect needs to have knowledge of all the different aspects of the technical Delivery as well as robust business knowledge. This includes the Software Architect.
Day to Day Responsibilities:
You are responsible for the end-to-end architecture of a Delivery, including its assembly and integration into the IT architecture principles defined with the client.
You define the structure of the system, its interfaces, and the principles that guide its organization, software design and implementation.
You are responsible for the management and mitigation of technical risks, ensuring that the Delivery services can be realistically delivered by the underlying technology components.
Required Skills and Experience:
Certification: Has or seeking IAF level 1.
Should be proficient in foundation, People Leadership, client acquisition & development, service & delivery and business leadership.
Should be experienced in technology awareness & leveraging and innovation & growth capability.
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.
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