Data analyst machine learning

2 weeks ago


New York, United States Randstad Full time

job summary:
Designing and maintaining data systems and databases; this includes fixing coding errors and other data-related problems. Mining data from primary and secondary sources, then reorganizing said data in a format that can be easily read by either human or machine. Using statistical tools to interpret data sets, paying particular attention to trends and patterns that could be valuable for diagnostic and predictive analytics efforts.

location: NEW YORK, New York
job type: Contract
salary: $60 - 65 per hour
work hours: 8am to 4pm
education: Bachelors

responsibilities:
JOB DESCRIPTION

Designing and maintaining data systems and databases; this includes fixing coding errors and other data-related problems. Mining data from primary and secondary sources, then reorganizing said data in a format that can be easily read by either human or machine. Using statistical tools to interpret data sets, paying particular attention to trends and patterns that could be valuable for diagnostic and predictive analytics efforts.

Required Skills/Experience (Skills that the successful candidate(s) must have)

  • Bachelor's degree in data science, data analytics, or a related field.

  • Proficiency in programming languages: SQL, Python and PySpark.

  • Minimum 3 years of experience with data visualization tools such as Power BI, Dax Queries, and best practices.

  • Experience with GenAI and large language models.

  • Must know how to analyze the root cause of dashboard errors.

  • Have experience in ML Ops and have strong coding background.

  • Have experience with Natural Language Processing (NLP).

  • Expertise in data mining and machine learning.

  • Knowledge or experience with A/B Testing.

  • Working knowledge of designing, training, and implementing machine learning models.

  • Familiarity with cloud-based infrastructure.

  • 7 or more years of experience in data science and machine learning engineering.
Additional Skills (Skills that are a plus, but not required)

  • Master's degree or Ph.D. in a quantitative field, such as statistics, computer science, mathematics, or engineering.

  • Azure Databrick Data Engineer Certification is a plus.

  • Experience with big data analytics technologies such as Spark and Hadoop.
Responsibilities

  • Collaborate with business stakeholders to understand their requirements and translate them into technical specifications.

  • Communicate insights and findings to business stakeholders.

  • Build, deploy, and maintain data management systems and back-end data infrastructure for our machine learning pipeline.

  • Build dashboards and analyze the root cause of dashboard malfunctions.

  • Perform data mining, exploration, and analysis.

  • Create data visualizations, reports, dashboards, and data audits.

  • Design, train, and implement machine learning algorithms.

  • Leverage predictive models to optimize customer experiences.
qualifications:
  • Experience level: Experienced
  • Minimum 5 years of experience
  • Education: Bachelors

skills: Machine Learning Python SQL spark

Equal Opportunity Employer: Race, Color, Religion, Sex, Sexual Orientation, Gender Identity, National Origin, Age, Genetic Information, Disability, Protected Veteran Status, or any other legally protected group status.

At Randstad Digital, we welcome people of all abilities and want to ensure that our hiring and interview process meets the needs of all applicants. If you require a reasonable accommodation to make your application or interview experience a great one, please contact HRsupport@randstadusa.com.

Pay offered to a successful candidate will be based on several factors including the candidate's education, work experience, work location, specific job duties, certifications, etc. In addition, Randstad Digital offers a comprehensive benefits package, including health, an incentive and recognition program, and 401K contribution (all benefits are based on eligibility).

This posting is open for thirty (30) days.

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