Data Science Architect/Manager-Artificial Intelligence
Limited immigration sponsorship may be available.Work you'll do
At Deloitte you will manage and deliver components of client engagements that identify, design, and implement technology and creative business solutions for large companies. Key responsibilities will include:
- Architect, position, design, develop and deploy enterprise solutions which include components across the Artificial Intelligence spectrum such as Chatbots, Virtual Assistants, Machine Learning, Computer Vision and Cognitive Services
- Manage teams in the identification of business requirements, functional design, process design (including scenario design, flow mapping), prototyping, testing, training, defining support procedures
- Formulate planning, budgeting, forecasting, and reporting strategies
- Manage full life cycle implementations
- Develop statements of work and/or client proposals
- Identify business opportunities to increase usability and profitability of information architecture
- Experience with program leadership, governance and change enablement
- Develop and manage vendor relationships
- Lead workshops for client education
- Manage resources and budget on client projects
- Assist and drive the team by providing oversight
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 Analytics & Cognitive 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.
Analytics & Cognitive 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
- 6+ years of relevant work experience
- 2+ years of experience leading and managing project teams
- At least 2 years of experience working with quantitative modeling (design, development & 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
- 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
- Travel up to 50% of the time (Monday - Thursday/Friday). (While 50% of travel is a requirement of the role, due to COVID-19, non-essential travel has been suspended until further notice.)
- 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
- Demonstrated expertise in at least one of the following: machine learning, deep learning, time-series modeling, propensity and prediction, behavioral nudges, recommenders, anomaly detection, segmentation, AI architecture, AI interface design
- Formal training in one or many of the following: signal processing, optimization, machine learning, linear algebra
- Expertise in at least one functional application preferred (e.g., prediction models, behavioral analytics, etc.)
- 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, Google Cloud Platform, Azure)
- Familiarity with Scala, Java, C++, or other similar technological support languages
- Expertise in 2+ domains preferred (e.g., Customer & Marketing, Finance, M&A, Operations, Pricing, Risk, Supply Chain, Workforce, etc.). Example of expertise includes:
- Supply Chain: Knowledge of operations, manufacturing, quality, or operations strategy for pharmaceutical, biotechnology and medical device organizations
- Payments: Experience with use cases such as fraud detection, cashier-less stores, hyper-personalized credit scores, enhanced customer service, etc.
- Customer: Experience with use cases such as reduce customer churn, accurately price products / services, increase up-sell / cross-sell, reduce service center call times, etc.
- HR: Experience with use cases such as improve workforce / role matching, workforce optimization, increase learning effectiveness, align total rewards by employee type, etc.
- IT: Experience with use cases such as optimize infrastructure use, optimize system / application performance, reduce IT security breaches, etc.
- Risk: Experience with use cases such as improve safety/standards compliance, improve fraud detection, improve regulatory compliance
- Operations: Experience with use cases such as eliminate underperforming SKUs, optimize fleet size and logistics, optimize inventory management
- Strong experience running pursuits
- Ability to communicate complex quantitative analysis in a concise and actionable manner
- Ability to work independently, manage small engagements or parts of large engagements
- Strong oral and written communication skills, including presentation skills (MS Visio, MS PowerPoint) (US Practitioners)
- Strong problem solving and troubleshooting skills with the ability to exercise mature judgement
- An advanced degree in the area of specialization is preferred