Data Scientist
Do you have a passion for artificial intelligence, machine learning, and data analysis? Do you yearn to have the impact of your work recognized and valued by more than just your development team?
If yes, we have just the role for you.
In Deloittes Audit and Assurance business, we make businesses and markets better. An audit is more than an obligation; it is an opportunity to see further and deeper into businesses. In our role as independent auditors, we enhance trust in the companies we audit, helping a multitrillion dollar capital markets system function with greater confidence. As we aspire to the very highest standards of audit quality, we deliver deeper insights that can help clients become more effective organizations.
You will be joining our collaborative Data Science team which leverages the most advanced technologies in machine learning and artificial intelligence to achieve the Deloitte Audit and Assurance vision of an AI-enabled audit. Some of our current projects focus on generative AI, prompt engineering, LLMs, anomaly detection, clustering, and knowledge graphs.
As a Data Scientist, you will be supporting the Data Science group and actively participating in the entire lifecycle of a data science project, including exploratory data analysis, feature engineering, model creation, and model optimization to boost performance and accuracy. It is important that the person in this role is proactive and independent. You should be a problem solver with an open mind and an eagerness to pick up new skills.
Specifically, you will be expected to:
Develop, test, and deploy machine learning/AI models
Collaborate daily with Data Science Managers and Senior Data Scientists to receive guidance and feedback on your work to develop your skills and ensure alignment with workstream objectives
Be a contributor to the planning and direction of a project and effectively prioritize your tasks and objectives
Contribute to internal discussions on emerging machine learning methodologies
Qualifications
Required:
2+ years of relevant experience
Undergraduate degree in a quantitative field (computer science, engineering, mathematics, physics, machine learning, statistics)
Experience using Python and relevant libraries (NumPy, Pandas, Scikit-learn, etc.)
Coursework related to machine learning, deep learning, and programming
At least an introductory understanding of LLMs and prompt engineering
Hands-on application experience using common machine learning frameworks such as TensorFlow, PyTorch, OpenAI, and LangChain
Demonstrated ability to write high-quality code
Demonstrated ability to develop machine learning models
- Ability to travel as needed (<25%)
Preferred:
3+ years of relevant experience
Masters degree in a quantitative field (computer science, engineering, mathematics, physics, machine learning, statistics)
Relevant work experience (internships, school jobs, etc.)
Familiarity with the Microsoft Azure cloud-based ecosystem, including Azure DevOps
Familiarity with machine learning model development life cycles
Experience with version control practices and tools (Git, etc.)
Public AI-related projects you have developed available on GitHub