Data Science Consultant at Capgemini

The AI & 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, including Media & Entertainment, High Tech, Automotive, Consumer Products & Retail,   Industrial Products, Manufacturing, Telecom, Aerospace & Defense, and Energy & Utilities.
The AI & Analytics group is the fastest growing digital practice at Capgemini demanding agile innovation. As part of the AI & 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 AI & Analytics practice group at Capgemini is the best place to grow your career.
Role & Responsibilities:
Work in a collaborative environment with global teams to drive client engagements in a broad range of industries to design and build scalable AI and Machine Learning solutions to solve business problems and create value by leveraging client data
Work with team to quickly understand client needs, develop solutions, and collaboratively present findings to client executives        
Collaborate with team to provide data-driven recommendations and solutions to clients by clearly articulating complex technical concepts through generation and delivery of presentations  
Analyze and model both structured and unstructured data to generate value
Use industry expertise and data science experience to uncover new opportunities with clients’ data
Qualifications
2-4 years industry experience, with work in a quant or data scientist field preferred
Master’s degree or PhD in Computer Science, Statistics, Economics, Mathematics, or other closely related field
Excellent team-oriented and interpersonal skills, with a strong interest for consulting
Outstanding communication skills with the ability to clearly articulate findings and present solutions to business partners
Strong understanding and application of statistical methods and skills: distributions, variance and correlation analysis, A/B testing, and regression
Expertise in machine learning algorithms and experience using the following ML techniques: Logistic Regression, Decision Trees, Random Forests, Gradient Boosting, SVMs, Time Series, Clustering, Linear Regression
Solid coding skills in at least one language, preferably Python or R
Experience with common data science packages (python: scikit-learn, matplotlib, pandas, numpy…// R: CARET, xgboost, gbm, ggplot, plotly, dply) or platforms (Azure AutoML, SageMaker, H2O.ai) 
Experience working with databases (SQL, Hive, MongoDB) 
Preferred Qualifications
Deep Learning experience (NLP/Computer Vision): experience using Pytorch, Tensorfllow or Keras
Experience working with big data distributed programming languages, and ecosystems: Spark, Hadoop, MapReduce, Pig, Kafka
Familiarity with Cloud-based environments such as AWS (S3/EC2), Azure, Google Cloud 
Knowledge of other coding languages such as Java, Matlab, SAS, C++
Experience with NLP, sentiment analysis, topic modelling  
Graph Theory and Graph databases (Neo4j)
Experience Skilled with building and deploying predictive models and experience building 
Additional requirements
Skills and experience with building data pipelines with SQL and ideally AWS tools such as Glue, Athena and Kinesis
Skills with Python
Some experience in building data pipelines, which source data from high-volume application and infrastructure event logs (as well as DB connectivity), would be a plus- sources such as Splunk or
New Relic would be a big plus
Some experience in data analysis
Good understanding of data models
Some exposure to analytics/ML/AI/AIOps and experience working as a data engineer in support of data scientists would be a plus 
Experience as a Data Engineer on an AIOPs project would be a plus
We Offer
Full medical, dental, vision, dental plans AND life insurance (they begin day one!)
Seven company-paid holidays + 2 personal days (determined by when you begin)
401(K) that you can participate in day one – fully vested after 12 months! 
Ten sick days per year for your own illness or for family needs
Long- and short-term disability
Employee Assistance programs and Employee Assistance Programs
Maternity & Paternity Leave
Adoption Assistance
Education Expense Reimbursement
Commuter Benefits