Deloitte Data Scientist in San Jose, California
Are you an experienced, passionate pioneer in technology? An industry solutions professional who wants to work in a collaborative environment. As an experienced Data Scientist, you will have the ability to share new ideas and collaborate on projects as a consultant without the extensive demands of travel. If so, consider an opportunity with Deloitte under our Project Delivery Talent Model. Project Delivery Model (PDM) is a talent model that is tailored specifically for long-term, onsite client service delivery. PDM practitioners are local to project locations, minimizing extensive travel, and provides you with a full career path within the firm.
Work you'll do/Responsibilities
The Analytics team is responsible for collecting, analyzing, and reporting on customer insights. From this data we generate insights into how customers interact with our products and use these insights to drive improvements to user-facing features.
We are looking for an extraordinary engineer to join the worldwide business development and strategy team. This is an opportunity to join a fast-paced team that plays a key role in the overall success of our organization through technology enablement. You'll play a critical part in driving our technology vision forward and ensuring that we execute across multiple initiatives.
As a part of the US Strategy & Analytics Offering Portfolio, the AI & Data Operations offering provides managed AI, Intelligent Automation, and Data DevOps services across the advise-implement-operate spectrum.
Bachelor's degree, preferably in Computer Science, Information Technology, Computer Engineering, or related IT discipline; or equivalent experience
Limited immigration sponsorship may be available
Ability to travel 10%, on average, based on the work you do and the clients and industries/sectors you serve
Lead ML/Data Scientist
A minimum of 5+ years of experience as a data scientist or machine learning engineer, from experimentation and prototyping to deployment
Experienced in applying thought leadership around AI/ML capabilities to drive new use cases and architectural decisions
In-depth and advanced understanding of machine learning and deep learning basics. Experience with machine learning and deep learning modeling in one or more of the following areas: anomaly detection, forecasting, causal inference, NLP, data mining or content analysis
Expertise in software engineering and skillful hands-on implementation with Python and Pyspark
Experience in design, implementation and delivery of scalable build/test/release agile software development cycle
Expertise with machine learning and deep learning packages and framework.
Advanced experience with big data technologies, such as Hadoop and Spark for large scale datasets. Well-versed in SQL languages
Experience applying AI/ML concepts and models to data and analytics projects including advanced analytics capabilities tied to data management and data integration work (e.g. data anomalies, forecast patterns, recommend rule patterns, etc.)
Ability to communicate effectively (written and spoken)
Ability to work with the multi-location development teams and self-manage individual and others work
• Proficiency in Python (experience with PySpark a plus) and SQL
• Proficiency in working with large datasets
Manage raw data, query/mining, and create analysis/databases/worksheets/Keynote summaries
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.