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Jobs · Business Development · Washington

Data Sci - Tech Con - AI and Data - Govt and Public Sector - Manager - Multiple Positions - 1714802

EY · Seattle, WA · 2 wk ago
On-siteBusiness Development$197k/yrFull-time

About the role

We’ll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world.

Responsibilities

  • Provide full range of consulting services to help State, Local and Education clients implement new ideas to help achieve their mission outcomes by delivering a unique perspective on how data science and analytics can transform and improve their entire organization.
  • Apply data mining and statistical analysis techniques like hypothesis testing, segmentation, and modelling to analyze large amounts of data.
  • Deliver the latest data science and big data technologies and practices to design, build and maintain scalable and robust solutions that unify, enrich and analyze data from multiple sources.
  • Help clients make data-driven decisions by working with structured and unstructured data sets, building out predictive models and advise clients on data mining leading practices.
  • Unify, enrich, and analyze client data to derive new insights and opportunities.
  • Leverage in-house data platforms as needed and recommend and build new data platforms/solutions as required to exceed client’s requirements.
  • Build and apply data analysis algorithms (data mining, statistics, machine learning, natural language processing, sentiment analysis, text mining, etc.) as appropriate.
  • Communicate findings, recommendations, and opportunities to clients to improve data systems and solutions.
  • Apply data driven approach (KPIs) in tying technology solutions to specific business outcomes.
  • Share leading practices and insights about current industry or subject-matter topics with EY US leaders, proposal teams and clients.

Requirements

  • Must have a Bachelor's degree in Mathematics, Information Systems, Statistics, Operations Research, Analytics, Computer Science, Engineering, Data Science, Machine Learning, or a related field, and 5 years of progressive, post-baccalaureate work experience. Alternatively, will accept a Master's degree in Mathematics, Information Systems, Statistics, Operations Research, Analytics, Computer Science, Engineering, Data Science, Machine Learning, or a related field and 4 years of work experience.
  • Must have 4 years of advisory and/or consulting experience.
  • Must have 4 years hands-on experience with one or a combination of the following: data science, big data, and/or data engineering.
  • Must have 3 years of experience connecting data sources and structures in one or a combination of any of the following: APIs, NoSQL, RDBMS, Hadoop, S3, SQL, Hive, Pig, and/or Blob Storage.
  • Must have 3 years of experience with advanced statistical modeling.
  • Must have 2 years of experience in at least one of the following: R, Python, Java, C#, or Scala.
  • Must have 2 years of experience in each of the following:
    • - machine learning such as k-NN, naive bayes, decision trees, or SVM
    • - data mining and statistical tools
    • - pattern recognition and predictive modelling
    • - recommendation engines, scoring systems, A/B testing
    • - setting up data and experimental platforms
  • Must have 2 years of hands-on experience with various big data technologies in at least one of the following ecosystems: Google, AWS, or Microsoft.
  • Must have 4 years of experience working with tools/libraries including with one or combination of any of the following: Python, Panda, and/or R.
  • Must have 2 years of experience of leading, coaching, mentoring and performance assessment of all levels of staff.
  • Requires domestic travel up to 30% to serve client needs.

Qualifications

Employer will accept any suitable combination of education, training or experience.

Skills

Must have a Bachelor's degree in Mathematics, Information Systems, Statistics, Operations Research, Analytics, Computer Science, Engineering, Data Science, Machine Learning, or a related field, and 5 years of progressive, post-baccalaureate work experience. Alternatively, will accept a Master's degree in Mathematics, Information Systems, Statistics, Operations Research, Analytics, Computer Science, Engineering, Data Science, Machine Learning, or a related field and 4 years of work experience.

Must have 4 years of advisory and/or consulting experience.

Must have 4 years hands-on experience with one or a combination of the following: data science, big data, and/or data engineering.

Must have 3 years of experience connecting data sources and structures in one or a combination of any of the following: APIs, NoSQL, RDBMS, Hadoop, S3, SQL, Hive, Pig, and/or Blob Storage.

Must have 3 years of experience with advanced statistical modeling.

Must have 2 years of experience in at least one of the following: R, Python, Java, C#, or Scala.

Must have 2 years of experience in each of the following:

  • - machine learning such as k-NN, naive bayes, decision trees, or SVM
  • - data mining and statistical tools
  • - pattern recognition and predictive modelling
  • - recommendation engines, scoring systems, A/B testing
  • - setting up data and experimental platforms

Must have 2 years of hands-on experience with various big data technologies in at least one of the following ecosystems: Google, AWS, or Microsoft.

Must have 4 years of experience working with tools/libraries including with one or combination of any of the following: Python, Panda, and/or R.

Must have 2 years of experience of leading, coaching, mentoring and performance assessment of all levels of staff.

Requires domestic travel up to 30% to serve client needs.

Employer will accept any suitable combination of education, training or experience.

Benefits

Base salary for this job is $196,914.00 per year. In addition, our Total Rewards package includes medical and dental coverage, pension and 401(k) plans, and a wide range of paid time off options.

Pay

$196,914.00 per year

Schedule

Monday – Friday, 40 hours per week, 8:30 am – 5:30 pm.

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