W-2 Jobs Portal

  • 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:

    J36993

  • Specialized Area:

    Data Analyst

  • Job Title:

    Data Science

  • Location:

    Columbus,IN

  • Duration:

    13 Months

  • Domain Exposure:

    Manufacturing, Utilities/ Energy, Retail, Media/ Entertainment

  • 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)




Job Description

Job Description

Responsibilities Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions. Mine and analyze data from company databases to drive optimization and improvement of product development, marketing techniques and business strategies. Assess the effectiveness and accuracy of new data sources and data gathering techniques. Develop custom data models and algorithms to apply to data sets. Use predictive modeling to increase and optimize customer experiences, revenue generation, ad targeting and other business outcomes. Coordinate with different functional teams to implement models and monitor outcomes. Develop processes and tools to monitor and analyze model performance and data accuracy. Qualifications 5-7 years of experience manipulating data sets and building statistical models Master s or above on Statistics, Mathematics, Computer Science or another quantitative field Experience querying databases and using statistical computer languages: R, Python, SQL, etc. Experience using statistical computer languages (R, Python, SQL, etc.) to manipulate data and draw insights from large data sets. Experience creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc. Experience with distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, MySQL, etc. Experience with supervised and unsupervised machine learning algorithms for regression, classification, and clustering Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks. Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications. Knowledge and experience in statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, NLP/text mining, etc. Experience using AWS services: Redshift, S3, Spark, SageMaker, etc. Coding knowledge and experience with several languages: C, C++, Java, Scala Bonus Skills and Experience: Experience working with and creating data architectures. Packaging of analytics for deployment on a cloud service in a scalable manner Experience using Azure services: Azure SQL Datawarehouse, azure Data Lake, Azure ML, et


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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