Search Jobs


Data Scientist / United States of America

This job has expired or may no longer be taking applications, but other similar jobs are available.
 Click here to shortlist this job 1-CLICK Apply With Employer or Register Now
Location: United States of America

Location: Fully Remote

Contract Length: 6 Months (potential to extend)

Pay Rate: $58-63/hr

Job Description:

To provide dedicated people analytics support to Business Technology Solutions (BTS) to address key business questions by leveraging various data mining & science approaches.

Major Responsibilities:

  • The Data Scientist will be responsible for designing, executing and explaining analytical solutions to BTS business questions in the people analytics space.
  • The Data Scientist will have end-to-end ownership of executing analyses, including identifying relevant tables and fields, joining and filtering to select the relevant data, applying business logic to tailor data to address the question, and identifying patterns suggestive of useful insights via statistics, machine learning, and operations research techniques.
  • Business questions will include data mining to uncover opportunities to enhance efforts in retention, recruitment/talent acquisition, and development of company BTS employees.
  • The Data Scientist will be embedded within the People Analytics team within the company talent organization and will adhere to all applicable standard operating procedures (SOPs) with respect to the handling and use of data related to employees.
  • The Data Scientist will work closely with BTS stakeholders including BTS Analytics and Information Strategy leadership to develop and execute analytics to address defined business questions.

Core Job Responsibilities:

  • Work with stakeholders to define business questions, requirements, timelines, objectives, and success criteria
  • Examine relevant data and quickly develop an analytics plan that will answer key business questions and create value for clients
  • Work with data sets of varying degrees of size and complexity, including both structured and unstructured data
  • Transform individual-level and transaction-level employee data into insightful summaries that address the business question, aggregated to protect individual identities. This includes processing, cleansing, and verifying the integrity of data used for analysis.
  • Partner with the BTS analytics team who will visualize the summarized data in reporting to BTS leadership to ensure smooth handover and correct presentation of results and implications.
  • Develop analytical solutions by using and applying appropriate methodology - including, but not limited to, regression, forecasting, clustering, decision trees, simulation, optimization, machine learning, and neural networks
  • Design systems and approach to operationalize models for machine learning.


  • Bachelor's degree required in quantitative fields such as Statistics, Engineering, Operations Research, Computer Science or Economics. Master's preferred. PhD a plus.
  • 3+ years' progressive business experiences in people analytics, marketing analytics, data analysis, data engineering and predictive modeling or strong academic background.
  • Strong algorithmic design skills. Execute analytical experiments methodically while outputting reproducible research.
  • Demonstrated expertise in SQL and Relational databases ((Oracle, Teradata etc.).
  • Demonstrated proficiency in Python, R, BI tools (Power BI, Qlik sense) and IDEs like Jupyter.
  • Ability to develop advanced machine learning models using scikit-learn, Keras, or other machine learning frameworks (oversight and guidance will be available from a Senior Data Scientist within the BTS Analytics team)
  • Experience with big data technologies like Hive, Impala, Hue etc.,
  • Experience in People/Talent datasets like Workday and Taleo a big plus.
  • Strong problem solving and interpersonal skills and ability to work as part of a diverse team including Human Capital Strategy and BTS.
  • Bring a strong entrepreneurial spirit and ability to think dynamically.
  • Strong communication skills, written and verbal.
  • Project management experience; solid attention to detail and operational focus.

Required Skills/Experience:

  • Able to independently translate English language questions and hypotheses into logical data models and business logic using available data (& data dictionary).
  • Able to create materialized views from an Oracle Database using SQL by joining tables and applying hypothesis-driven business logic with effective quality control (checking for dropped records, that # of records make sense, that calculated outputs are reasonable considering other similar reporting in production)
  • Some experience with data science techniques including clustering and feature importance analysis to mine data for relevant and credible insights in response to business questions.
  • 3 or more years' experience executing data analysis with corporate clients or within a corporation
  • SQL Development experience with an Oracle database
  • Some experience executing clustering and/or feature importance analysis in Python
  • Strong attention to detail and quality

Preferred Skills/Experience:

  • Effectively combines data science techniques including clustering and feature importance analysis with domain expertise (can be established during the contract through active listening) to mine data for insights in response to business questions. Execute analytical experiments methodically while outputting reproducible research.
  • Domain expertise and experience with data describing people and people-related events in a corporate context, including but not limited to HR/Workday, Talent Acquisition/Taleo
  • Degree in a quantitative field such as Statistics, Engineering, Operations Research, Computer Science or Economics.
  • Comfort inferring likely data definitions based on comparisons to other fields and critical thinking (e.g. if a field name is not as expected but sample records have an identifiable pattern that is expected and the field joins well with a field in another table that is named as expected, probably the field with the unexpected name bears some relationship to the field with the expected name)
  • Experience modeling data in Tableau

How to Apply

Latest Jobs -
© All rights reserved, 2001 - 2023