Data Science Senior 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
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 consultants
Assist in growing data science practice by meeting business goals through client prospecting, responding to proposals, identifying and closing opportunities within identified client accounts
Qualifications
5-8 years professional work experience as a data scientist or on advanced analytics/statistics projects
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
Preferred Qualifications
Experience with Deep Learning methods in NLP & computer vision, sentiment analysis, topic modeling and graph theory and databases
Experience with common data science tools such as Python, R, Pytorch, TensorFlow, Keras, NLTK, Spacy, or Neo4j, and a good understanding of modelling platforms (Azure AutoML, SageMaker, DataBricks, DataRobot and H2O.ai) 
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 building and deploying predictive and prescriptive analytics models
Additional requirements
Strong leadership skills and good communicator
Comprehensive knowledge of AWS architecture, tools, principles and integration methods- ESPECIALLY in data engineering, data lake and data pipeline space
Experienced in designing and building data pipelines, which source data from high-volume application and infrastructure event logs
Experience in sourcing data from SPLUNK and/or New Relic would be a big plus
Knowledge and experience with designing and building high volume data pipelines for data lakes and data warehouses in AWS cloud using tools such as: pure SQL, Python, Glue, Athena and Kinesis
Knowledge and experience with AWS persistent data storage tools such as S3, RDS and Redshift
Experienced in optimally connecting data pipelines to high-volume event log sources as well as DB connectivity- sources such as Splunk or New Relic would be a big plus
Experienced in data analysis
Experienced in defining data models
Background in mentoring Jr Data Engineer(s) to complete specific tasks on time
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
Flexible Spending Accounts, Adoption Assistance
Perks at Work
Back up Child and Adult/Elder Care