Apply data mining techniques, performing statistical analysis and building high quantity prediction systems integrated with tax technology products
Assist businesses navigate the digital age of tax transparency alongside new trends in tax compliance and tax audit methods
Identify complex problems and reviewing related information to develop and evaluate options, and provide data-driven business recommendations to clients
Decrease the cost of managing data and increasing the value of existing data
Process, cleanse and verify the integrity of data used for analysis and enhance data collection procedures to include information that is relevant for building analytic system
Select features and, build and optimize classifiers using machine learning techniques
Support various client projects, ranging from assisting in the production of leading edge machine models, to designing and implementing robust data pipelines that can handle data at a multinational, enterprise scale
Manage and motivate teams of professionals with diverse skills and backgrounds
Consistently deliver quality client services by monitoring progress
Demonstrate in-depth technical capabilities and professional knowledge

Requirements

Bachelor’s degree in Accounting, Computer Science, Data Science, Engineering, Management Information Systems, Statistics, or a related field and 5 years of progressive, post-baccalaureate related work experience
Master’s degree in Accounting, Computer Science, Data Science, Engineering, Management Information Systems, Statistics, or a related field and 3 years of related work experience
3 years of experience working in a professional services firm, a consulting firm, or a mid-sized/regional to large-sized/national public accounting firm
3 years of experience in the management and manipulation of large datasets, both structured and unstructured, of which 1 year of experience must be with tax or accounting-related datasets
3 years of experience with machine learning techniques and algorithms, including at least one of the following: Linear/Logistic Regression, k-NN, Naïve Bayes, Support Vector Machines (SVM), and/or Decision Forests
2 years of experience managing and/or analyzing data using at least one of the following: - SQL and NoSQL; - SQL Server; or - MongoDB
1 year of experience with using the Python toolkit (Pandas, NumPy, and/or Jupyter Notebooks)
1 year of experience with distributed file systems including Apache Spark
1 years of experience designing and implementing ETL solutions for tools, including at least one of the following: Alteryx, SSIS, DataStage, Informatica, Talend, and/or Pentaho
1 years of experience with data visualization tools, such as Power BI, Tableau, and/or D3.js
1 year of experience with data science programming languages, including, Python and R
1 year of experience managing junior data and data analytics professionals, including setting goals, assigning work, and reviewing performance
Requires domestic travel up to 10%, to serve client needs

Benefits

medical and dental coverage
pension and 401(k) plans
wide range of paid time off options
flexible vacation policy
designated EY Paid Holidays
Winter/Summer breaks
Personal/Family Care
other leaves of absence

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

data miningstatistical analysismachine learningdata manipulationETL solutionsdata visualizationPythonSQLNoSQLApache Spark

Soft Skills

problem solvingteam managementclient servicecommunicationmotivationanalytical thinkingdecision makingorganizational skillscollaborationleadership