Senior Data Scientist (Remote)

VincentBenjamin

Scottsdale Arizona

United States

Information Technology
(No Timezone Provided)

***No third-party or H1-B candidates will be accepted.***

Title: Senior Data Scientist

Location: Remote

Hiring Model: Initial full-time, six-month contract with possibility to convert to a permanent employee

About the Client:

Our client is a technology and services company that provides the data foundation for the world's best companies. They are a leader in identity and the ethical use of data for more than five decades.

The Role:

We are searching for a strategic and inquisitive senior data scientist to develop and run with data-centered projects. In keeping with this overarching aim, the senior data scientist will be required to outline work requirements, assign tasks to junior staff, and monitor performance within the team. You should also harness your mastery of Data Science to consult on various aspects of these and other projects.

To be successful as a senior data scientist, you should use data to ultimately inform and promote the company's expansion. Top-notch senior data scientists will assume a prominent role in the development of junior staff.

Responsibilities:

  • Formulating, suggesting, and managing data-driven projects which are geared at furthering the business's interests.
  • Delegating tasks to Junior Data Scientists in order to realize the successful completion of projects.
  • Selecting and employing advanced statistical procedures to obtain actionable insights.
  • Cross-validating models to ensure their generalizability.
  • Producing and disseminating non-technical reports that detail the successes and limitations of each project.
  • Suggesting ways in which insights obtained might be used to inform business strategies.
  • Staying informed about developments in Data Science and adjacent fields to ensure that outputs are always relevant.

Required Skills and Qualifications:

  • Advanced degree in data science, statistics, computer science, similar, OR equivalent experience.
  • 3+ years of experience building, testing and deploying production-ready models in python or similar language
  • Strong experience in Python (scikit learn) or Spark (MLLib) for machine learning
  • 2+ years of experience in building and deploying models at scale using Spark/Pyspark systems in a distributed computing environment
  • At least 2+ years of experience building ETL transformation, modeling & mlops pipelines
  • Experience applying statistics and data science tools on large datasets. Extensive experience with data preparation (normalization, scaling, etc.) for modeling
  • Working knowledge of supervised vs. unsupervised learning algorithms, including linear/logistic regression, neural networks/deep learning, SVM, decision trees (bagging, random forests, boosting), XG Boost, clustering, regression, and dimensionality reduction techniques
  • SQL mastery, including techniques for writing efficient code over large datasets
  • Ability to leverage critical data-driven thinking and enthusiasm for translating data into actionable insight to generate consistently accurate and useful analysis and models
  • Balance desire for quantitative rigor with realities of inconsistent business data
  • Compliance with prevailing ethical standards.

Senior Data Scientist (Remote)

VincentBenjamin

Scottsdale Arizona

United States

Information Technology

(No Timezone Provided)

***No third-party or H1-B candidates will be accepted.***

Title: Senior Data Scientist

Location: Remote

Hiring Model: Initial full-time, six-month contract with possibility to convert to a permanent employee

About the Client:

Our client is a technology and services company that provides the data foundation for the world's best companies. They are a leader in identity and the ethical use of data for more than five decades.

The Role:

We are searching for a strategic and inquisitive senior data scientist to develop and run with data-centered projects. In keeping with this overarching aim, the senior data scientist will be required to outline work requirements, assign tasks to junior staff, and monitor performance within the team. You should also harness your mastery of Data Science to consult on various aspects of these and other projects.

To be successful as a senior data scientist, you should use data to ultimately inform and promote the company's expansion. Top-notch senior data scientists will assume a prominent role in the development of junior staff.

Responsibilities:

  • Formulating, suggesting, and managing data-driven projects which are geared at furthering the business's interests.
  • Delegating tasks to Junior Data Scientists in order to realize the successful completion of projects.
  • Selecting and employing advanced statistical procedures to obtain actionable insights.
  • Cross-validating models to ensure their generalizability.
  • Producing and disseminating non-technical reports that detail the successes and limitations of each project.
  • Suggesting ways in which insights obtained might be used to inform business strategies.
  • Staying informed about developments in Data Science and adjacent fields to ensure that outputs are always relevant.

Required Skills and Qualifications:

  • Advanced degree in data science, statistics, computer science, similar, OR equivalent experience.
  • 3+ years of experience building, testing and deploying production-ready models in python or similar language
  • Strong experience in Python (scikit learn) or Spark (MLLib) for machine learning
  • 2+ years of experience in building and deploying models at scale using Spark/Pyspark systems in a distributed computing environment
  • At least 2+ years of experience building ETL transformation, modeling & mlops pipelines
  • Experience applying statistics and data science tools on large datasets. Extensive experience with data preparation (normalization, scaling, etc.) for modeling
  • Working knowledge of supervised vs. unsupervised learning algorithms, including linear/logistic regression, neural networks/deep learning, SVM, decision trees (bagging, random forests, boosting), XG Boost, clustering, regression, and dimensionality reduction techniques
  • SQL mastery, including techniques for writing efficient code over large datasets
  • Ability to leverage critical data-driven thinking and enthusiasm for translating data into actionable insight to generate consistently accurate and useful analysis and models
  • Balance desire for quantitative rigor with realities of inconsistent business data
  • Compliance with prevailing ethical standards.