Artificial Intelligence and Data Science - Manager - Tech Consulting at Ernst & Young in New York, NY
The opportunity You will help our clients navigate the complex world of modern data science and analytics. We'll look to you to provide our clients with a unique business perspective on how data science and analytics can transform and improve their entire organization - starting with key business issues they face. This is a high growth, high visibility area with plenty of opportunities to enhance your skillset and build your career. Your key responsibilities You'll spend most of your time working with a wide variety of clients to deliver the latest data science and big data technologies and practices to design, build and maintain scalable and robust solutions that unify, enrich and analyse data from multiple sources. Skills and attributes for success Applying data mining and statistical analysis techniques like hypothesis testing, segmentation and modelling to analyze large amounts of data Helping our clients make data-driven decisions by working with structured and unstructured data sets, building out predictive models and advising our clients on data mining leading practices Building and applying data analysis algorithms (data mining, statistics, machine learning, natural language processing, sentiment analysis, text mining, etc.) as appropriate Designing, architecting and developing solutions leveraging big data technology (Open Source, Hortonworks, AWS or Microsoft) to ingest, process and analyze large, disparate data sets to exceed business requirements Unifying, enriching and analyzing customer data to derive new insights and opportunities Leveraging in-house data platforms as needed and recommending and building new data platforms/solutions as required to exceed business requirements Clearly communicating findings, recommendations and opportunities to improve data systems and solutions Demonstrating deep understanding of and ability to teach data science, concepts, tools, features, functions and benefits of different approaches to apply them Seeking out information to learn about emerging methodologies and technologies Clarifying problems by driving to understand the true issue Looking for opportunities for improving methods and outcomes Applying data driven approach (KPIs) in tying technology solutions to specific business outcomes Collaborating, influencing and building consensus through constructive relationships and effective listening Solving problems by incorporating data into decision making To qualify for the role you must have A bachelor's degree and approximately six years of related work experience; or a master's degree and approximately five years of related work experience At least five years hands-on experience with data science, big data, and data engineering Extensive experience connecting to various data sources and structures:
APIs, NoSQL, RDBMS, Hadoop, S3, Blob Storage, etc. Deep understanding of statistical modeling as well as ETL, data ingestion/cleansing and engineering skills Ability to set up data and experimental platforms R or SAS, Python, Java/C# and Scala SQL, Hive, Pig are required Machine learning using k-NN, naive bayes, decision trees, SVM experience required Experience using data mining and statistical tools Solid pattern recognition and predictive modelling skills Recommendation engines, scoring systems, A/B testing Must have worked with multiple tools/libraries such as Weka, NumPy, PyMongo, R, etc. Thorough business understanding of data science application and ability to communicate with key decision-makers Hands-on experience with various big data technologies in one or more ecosystems (Hadoop, AWS or Microsoft) Communication is essential, must be able to listen and understand the question and develop and deliver clear insights. Outstanding team player. Independent and able to manage and prioritize workload. Ability to quickly and positively adapt to change. A valid driver's license in the US; willingness and ability to travel to meet client needs. Ideally, you'll also have Bachelor's Degree or above in mathematics, information systems, statistics, computer science, or related disciplines Experience with Azure Data Factory and AzureML a plus
Salary Range:
$200K -- $250K
Minimum Qualification
Data Science & Machine Learning, Business Intelligence & Analytics, Technology ManagementEstimated Salary: $20 to $28 per hour based on qualifications.
APIs, NoSQL, RDBMS, Hadoop, S3, Blob Storage, etc. Deep understanding of statistical modeling as well as ETL, data ingestion/cleansing and engineering skills Ability to set up data and experimental platforms R or SAS, Python, Java/C# and Scala SQL, Hive, Pig are required Machine learning using k-NN, naive bayes, decision trees, SVM experience required Experience using data mining and statistical tools Solid pattern recognition and predictive modelling skills Recommendation engines, scoring systems, A/B testing Must have worked with multiple tools/libraries such as Weka, NumPy, PyMongo, R, etc. Thorough business understanding of data science application and ability to communicate with key decision-makers Hands-on experience with various big data technologies in one or more ecosystems (Hadoop, AWS or Microsoft) Communication is essential, must be able to listen and understand the question and develop and deliver clear insights. Outstanding team player. Independent and able to manage and prioritize workload. Ability to quickly and positively adapt to change. A valid driver's license in the US; willingness and ability to travel to meet client needs. Ideally, you'll also have Bachelor's Degree or above in mathematics, information systems, statistics, computer science, or related disciplines Experience with Azure Data Factory and AzureML a plus
Salary Range:
$200K -- $250K
Minimum Qualification
Data Science & Machine Learning, Business Intelligence & Analytics, Technology ManagementEstimated Salary: $20 to $28 per hour based on qualifications.
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