Deloitte Data Science, Senior Consultant - Applied Artificial Intelligence in Minneapolis, Minnesota
Data Science, Senior Consultant - Applied Artificial Intelligence
Work you'll do
AI Senior Consultants will architect, position, design, develop and deploy enterprise solutions which include components across the Artificial Intelligence spectrum such as Chatbots, Virtual Assistants, Machine Learning, and Cognitive Services (e.g. Vision/Image, Textual/Language processing).
Perform data studies and data discovery routines for video, voice, weblog, sensor, machine and social media data sources or mash ups of new and existing data sources.
AI & Data Engineering
In this age of disruption, organizations need to navigate the future with confidence, embracing decision making with clear, data-driven choices that deliver enterprise value in a dynamic business environment.
The AI & Data Engineering team leverages the power of data, analytics, robotics, science, and cognitive technologies to uncover hidden relationships from vast troves of data, generate insights, and inform decision-making. Together with the Strategy practice, our Strategy & Analytics portfolio helps clients transform their business by architecting organizational intelligence programs and differentiated strategies to win in their chosen markets.
AI & Data Engineering will work with our clients to:
Implement large-scale data ecosystems including data management, governance, and the integration of structured and unstructured data to generate insights leveraging cloud-based platforms
Leverage automation, cognitive and science-based techniques to manage data, predict scenarios, and prescribe actions
Drive operational efficiency by maintaining their data ecosystems, sourcing analytics expertise, and providing As-a-Service offerings for continuous insights and improvements
3+ years of relevant analytics consulting or industry experience
At least 2 years of experience working with quantitative modeling (design, development, and implementation) using 3+ types of algorithm (e.g., Decision Trees, Naive Bayes Classification, Ordinary Least Squares Regression, Logistic Regression, Support Vector Machines, Ensemble Methods, Clustering Algorithms, Principal Component Analysis, Singular Value Decomposition, Independent Component Analysis)
2+ years of experience using statistical computer languages (Python, SQL, R, SAS, etc.) to prepare data for analysis, visualize data as part of exploratory analysis, generate features, and other similar data science driven data handling
2+ years of experience leading workstreams or small teams
Demonstrated expertise with one full life cycle analytics engagement across strategy, design, and implementation
Bachelor's Degree in Engineering, Mathematics, Empirical Statistics, or 4 years equivalent professional experience
Ability to travel up to 50% on average, based on the work you do and the clients and industries/sectors you serve
Limited immigration sponsorship may be available.
Experience architecting, designing, developing and deploying enterprise solutions which include components across the Artificial Intelligence spectrum such as NLP, Chatbots, Virtual Assistants, Computer Vision, and Cognitive Services
Expertise in Python machine and deep learning frameworks and libraries, e.g. PyTorch, Keras, Tensorflow, Scikit-learn, Numpy, SciPy
Experience designing and implementing Apache Open Source (Kafka, Storm, Spark) frameworks to process end to end data management life cycle
Experience with Cloud services and ML tools e.g. (AWS, GCP, Azure)
Familiarity with Scala, Java, C++, or other similar technological support languages
Ability to work independently and manage multiple task assignments
Strong oral and written communication skills, including presentation skills (MS Visio, MS PowerPoint)
Strong problem solving and troubleshooting skills with the ability to exercise mature judgement
An advanced degree in the area of specialization
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability or protected veteran status, or any other legally protected basis, in accordance with applicable law.