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  • W-2 Open Positions Need to be Filled Immediately. Consultant must be on our company payroll, Corp-to-Corp (C2C) is not allowed.
Candidates encouraged to apply directly using this portal. We do not accept resumes from other company/ third-party recruiters

Job Overview

  • Job ID:

    J36268

  • Posted Date:

    09/19/2019

  • Specialized Area:

    Machine learning

  • Job Title:

    Machine learning Engineer

  • Location:

    San Jose,CA

  • Duration:

    8 Months

  • Domain Exposure:

    Healthcare, Pharmaceuticals, Insurance, Retail, Education

  • Work Authorization:

    US Citizen, Green Card, OPT-EAD, CPT, H-1B,
    H4-EAD, L2-EAD, GC-EAD

  • Client:

    To Be Discussed Later

  • Employment Type:

    W-2 (Consultant must be on our company payroll. C2C is not allowed)

  • Bench Recruiter:

    Vanessa Lynch




Job Description

RESPONSIBILITIES:

- Developing scalable data processing pipelines for analytical and predictive platform services

- Collaborate with other data scientists and engineers to find effective solutions to technical challenges

- Provide recommendations, guidance and options to support Pearson s GLP product development road map

- Work closely with engineers to build, test, deploy and troubleshoot machine learning / algorithm based software

QUALIFICATIONS:

- MSc or higher in computer science, statistics, mathematics, physical science, engineering, or a comparable related technical field

- 5+ years of industry experience in engineering, data science or related areas

- Demonstrated mastery in communication of technical ideas to non-technical audiences

- Ability to translate customer goals into practical engineering solutions

- Good understanding of foundational statistics concepts and algorithms: linear/logistic regression, random forest, boosting, NNs, etc.

- Strong programming skills with fluency in at least one of Python or R, Java, Scala, C/C++

- Ability to access, manage, transfer, integrate and analyze complex datasets, especially using SQL or map-reduce techniques

- Familiarity with libraries such as Spark ML, Tensor flow, scikit-learn, MLib, DLib, Pandas or others like H2O, Databricks


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Equal Opportunity Employer

DIGITAL TECHNOLOGIES LLC is an equal opportunity employer inclusive of female, minority, disability and veterans, (M/F/D/V). Hiring, promotion, transfer, compensation, benefits, discipline, termination and all other employment decisions are made without regard to race, color, religion, sex, sexual orientation, gender identity, age, disability, national origin, citizenship/immigration status, veteran status or any other protected status. DIGITAL TECHNOLOGIES LLC will not make any posting or employment decision that does not comply with applicable laws relating to labor and employment, equal opportunity, employment eligibility requirements or related matters. Nor will DIGITAL TECHNOLOGIES LLC require in a posting or otherwise U.S. citizenship or lawful permanent residency in the U.S. as a condition of employment except as necessary to comply with law, regulation, executive order, or federal, state, or local government contract


Equal Opportunity Employer

DIGITAL TECHNOLOGIES LLC is an equal opportunity employer inclusive of female, minority, disability and veterans, (M/F/D/V). Hiring, promotion, transfer, compensation, benefits, discipline, termination and all other employment decisions are made without regard to race, color, religion, sex, sexual orientation, gender identity, age, disability, national origin, citizenship/immigration status, veteran status or any other protected status. DIGITAL TECHNOLOGIES LLC will not make any posting or employment decision that does not comply with applicable laws relating to labor and employment, equal opportunity, employment eligibility requirements or related matters. Nor will DIGITAL TECHNOLOGIES LLC require in a posting or otherwise U.S. citizenship or lawful permanent residency in the U.S. as a condition of employment except as necessary to comply with law, regulation, executive order, or federal, state, or local government contract