Capgemini Data Science Manager in Lee's Summit, Missouri
Senior Applications Consultant - BA Data Scientist
Analysis and design, Data Science and Analytics. Creates and envisions the modeling data with the purpose of understanding and drawing conclusions. Delivers Data Science and Analytics, including algorithms, data models and automation, therein. Experienced in retail accelerators (i.e. pricing, promotions, market basket) and applied techniques for data processing and visualization. Creates approaches for confirming hypotheses and digging into analytical outcomes in pursuit of value.
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.
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.
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.
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.
A global leader in consulting, technology services and digital transformation, Capgemini is at the forefront of innovation to address the entire breadth of clients’ opportunities in the evolving world of cloud, digital and platforms. Building on its strong 50-year heritage and deep industry-specific expertise, Capgemini enables organizations to realize their business ambitions through an array of services from strategy to operations. Capgemini is driven by the conviction that the business value of technology comes from and through people. It is a multicultural company of 200,000 team members in over 40 countries. The Group reported 2017 global revenues of EUR 12.8 billion (about $14.4 billion USD at 2017 average rate).
Visit us at www.capgemini.com . People matter, results count.
Organization: I AND D US
Title: Data Science Manager
Location: MO-Lee%27s Summit
Requisition ID: 037297