Machine Learning Engineer

Employer
  • NTT Data

Job Description

145314

NTT DATA Services strives to hire exceptional, innovative and passionate individuals who want to grow with us. If you want to be part of an inclusive, adaptable, and forward-thinking organization, apply now.

We are currently seeking a Machine Learning Engineer to join our team in Irvin, Texas (US-TX), United States (US).

Role Responsibilities:

-Utilize predictive analytics and statistical tools, machine learning algorithms and big data tools
-Identify, analyze and interpret trends or patterns in complex data sets using various regression, classification or clustering ML approaches
-Good familiarity with classic ML approaches
-Create visualizations to visually represent data for consumption by different audiences

Basic Qualifications:

-5+ years SQL, R or Python, Spark, Hive
-5+ years Frameworks/libs: SciKit-learn, NLTK, Gensim, Pandas, NumPy, Matplotlib, SciKit

Preferences/nice to have:

-NLP exposure

-Hadoop, Spark, Elastic Stack, Git
-Frameworks/libs: TensorFlow, Keras, Spacy
-HTTP and invoking web-APIs
-Working in SCRUM methodology
-Business Domain knowledge: Finance & banking systems, Fraud, Payments
-Niches: Cognitive Computing, Natural Language Understanding

Education:

-Bachelor's degree in a technical discipline (preferably computer science) or equivalent experience

PAS2

INDFSINS

About NTT DATA Services

NTT DATA Services is a global business and IT services provider specializing in digital, cloud and automation across a comprehensive portfolio of consulting, applications, infrastructure and business process services. We are part of the NTT family of companies, a partner to 85 % of the Fortune 100.

NTT DATA Services is an equal opportunity employer and will consider all qualified applicants for employment without regard to race, gender, disability, age, veteran-status, sexual orientation, gender identity, or any other class protected by law. To learn more, please visit
. Furthermore, NTT DATA Services will make accommodations for eligible applicants on a case-by-case basis. Please email for assistance.

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