Tax Technology and Transformation - Advanced Technologies - Data Scientist - Staff

EY Studio+ Nederland•Dallas, NY

20h•Hybrid

About The Position

Tax Technology and Transformation provides services to help companies address the challenges posed by existing and emerging technologies, particularly the increasing data burden, by enhancing efficiency and transforming tax functions into cost-effective operations. The aim is to assist businesses in navigating the digital landscape of tax transparency, compliance, and audit methods while tackling pressing challenges. Key offerings include: digital tax transformation, tax applications-as-a-service, tax data improvement, analytics enhancement, and emerging technologies like robotic process automation (RPA), artificial intelligence (AI), and blockchain. Additionally, services encompass tax technology program mobilization, custom application development, strategy road mapping, implementation of direct and indirect tax systems, post-transaction operational services, and assessments of tax functions. In today's evolving corporate environment, implementing a transaction tax calculation engine is crucial for automating tax determination and compliance processes across various transactional systems, including ERP applications and custom solutions.

Requirements

A bachelor's degree in data science, information system, tax technology, management information systems or computer science or related field and a minimum of one year of related work experience
Approved technical certification, CPA license or membership to state Bar or progress to attaining those mentioned
A passionate interest in data science and its role in organization
Excellent communication and business writing skills
A natural flair for problem solving and an entrepreneurial approach to work
Strong organizational and time management skills, with exceptional client-serving consulting skills
Desire and demonstrated ability to provide leadership within a team
Willingness to travel as needed, and working in a balanced hybrid environment
Strong understanding of machine learning techniques and algorithms, such as Linear/Logistic Regression, k-NN, Naïve Bayes, Support Vector Machines (SVM), Random Forests, etc.
Strong command and up-to-date knowledge of the latest developments in the field of Artificial Intelligence, including but not limited to Generative AI, and AI Agents.
Hands-on experience with LLMs, and AI Agents
Strong working knowledge and at least 1-2 years of experience with Python
Strong knowledge and experience using the Python toolkit (Pandas, NumPy, Jupyter Notebooks, etc.) are essential
Experience with data visualization tools, such as PowerBI, Seaborn, Matplotlib, etc.
Experience with one of the following: SQL and NoSQL database technologies, SQL Server, MongoDB, Databricks, or Snowflakes
Strong scripting and programming skills.
Ability to write clean code and understand Object Oriented Programming concepts.

Nice To Haves

Experience with Apache Spark, Databricks, Snowflakes or other data tools
Experience working in the Microsoft Azure Cloud environment, AWS, GPT or other Cloud environment
Experience developing ETL solutions using SSIS or other tools
ERP experience, including SAP and/or Oracle-preferred but not required
Practical experience or strong theoretical understanding of neural networks and their applications

Responsibilities

Selecting features and building and optimizing classifiers using machine learning techniques
Large Language Models (LLM) prompting and deployment techniques
Designing and building AI Agents to automate and enhance complex business tasks
Integration of AI components into full-scale solutions to support business processes
Data mining using state-of-the-art methods
Enhancing data collection procedures to include information that is relevant for building analytic systems
Processing, cleansing and verifying the integrity of data used for analysis
Doing ad-hoc analysis and presenting results in a clear manner
Supporting various client projects, ranging from assisting in the production of leading-edge machine learning models, to designing and implementing robust data pipelines that can handle data at a multinational, enterprise scale.
Contributing and helping toward developing a highly trained team, all the while handling activities with a focus on quality and commercial value.
Maintaining our reputation as trusted advisors by taking on bold initiatives and owning new challenges.
Ownership of assigned tasks and monitoring them until completion, including documenting requirements, configuration, testing and debugging.
Ability to identify ways to automate manual tasks using existing financial or tax systems and emerging technologies
Ability to consolidate data to make analysis and planning more efficient
Focus on improving reporting capabilities to enhance our clients' ability to evaluate risk and capitalize on opportunities
Willingness to support project team members in any way needed to help ensure timely completion of deliverables