Inside Higher Ed
(Senior) Research Computing and Analytics Associate
Inside Higher Ed, Palo Alto, California, United States, 94306
Senior (Associate) Research Computing and Analytics Associate – Stanford GSB
Stanford Graduate School of Business (GSB) seeks either an Associate or Senior Associate to join the Data, Analytics, and Research Computing (DARC) team. The level (Associate or Senior Associate) will be determined by education and experience as reviewed by Human Resources. Overview As a (Senior) Research Computing and Analytics Associate, you will draw on technical knowledge and interpersonal skills to facilitate and accelerate academic research at Stanford GSB. You will collaborate with researchers, faculty, students, and staff to identify and develop innovative technical solutions to resolve research questions, and you will deliver learning opportunities and training resources to GSB researchers. Responsibilities Collaborate with faculty and researchers to understand research goals and help identify technical obstacles and solutions. Work with outside vendors to ensure secure and timely transfer of research data. Understand data types collected and how to integrate research workflows across databases and data warehouses. Research and suggest new toolsets/methods to improve data ingestion, storage, processing, and access. Contribute to guidelines, standards, and processes to ensure security of systems and data appropriate to risk. Monitor ETL processes, perform system audits, and proactively fix issues; support system performance. Serve as technical interface with software vendors and data providers to ensure researchers have effective data access in selected systems. Contribute to technical strategies and architectures to achieve research goals, using external vendors as needed. Participate in R&D to enhance the team’s capabilities, including tutorials, testing new data collection methods, and staying current with literature. Develop and deliver documentation and training for faculty and research staff. Minimum Requirements This role may be classified as either Associate or Senior Associate based on the applicant’s education and experience. Human Resources will determine the appropriate level. Desired Skills for the Associate Bachelor’s degree and a minimum of five years of relevant experience in computer science or engineering, or equivalent. Knowledge of data transfer, data warehousing, data storage technologies, and ETL for large datasets. Ability to support custom ETL, auditing, and scheduling programs. Experience with research software (R, Stata, Matlab, SAS, Julia, JavaScript). Experience with data processing at scale and understanding which tools to use when. Knowledge of relational databases and SQL. Ability to design and deploy scalable data ETL pipelines with existing and emerging technologies. Strong problem-solving, interpersonal, and communication skills. Experience in a research or academic setting (minimum 1 year). Additional Desired Skills for the Associate Bachelor's or Master’s in computer science, data science, statistics, or related field (Master’s preferred). Strong Python programming skills. Experience with large data transfers and ETL projects (Globus, rclone, SFTP); data warehouses. Knowledge of data security (deidentification, ACLs, IRB, etc.). Experience on interactive Linux and cloud platforms (AWS, BigQuery); familiarity with high-performance languages. Commitment to continual learning and professional growth; ability to work independently in a fast-paced environment. Senior Associate Additional Requirements Bachelor’s degree and at least seven years of relevant experience; Master’s preferred. Advanced data science and machine learning experience; familiarity with R, Stata, Matlab, SAS, Julia, JavaScript. Experience with data processing at scale and select appropriate tools; familiarity with text and image processing (OCR, NLP, regex, image classification). Ability to develop and deploy full-stack applications and API integrations for a research setting. Excellent problem-solving, interpersonal, and communication skills; continuous learner; service-oriented. Minimum three years in a research or academic setting applying data science and ML techniques. Compensation and Work Arrangement The expected pay range for this position is $111,142–$140,000 per year for the Associate and $145,282–$155,000 per year for the Senior Associate. This position is open to a hybrid work arrangement requiring on-site presence eight days per month, with on-site requirements during events. Stanford University pay ranges are a good faith estimate. Final pay is determined based on scope, qualifications, departmental budget, internal equity, location, and market data. The Cardinal at Work benefits program applies; specifics discussed during hiring. How to Apply Apply for this position by clicking the “Apply for Job” button. Please submit a cover letter and résumé along with your online application. EEO and Other Information Schedule: Full-time Job Code: 4777 Employee Status: Regular Grade: K Requisition ID: 105532 Work Arrangement: Hybrid Eligible
#J-18808-Ljbffr
Stanford Graduate School of Business (GSB) seeks either an Associate or Senior Associate to join the Data, Analytics, and Research Computing (DARC) team. The level (Associate or Senior Associate) will be determined by education and experience as reviewed by Human Resources. Overview As a (Senior) Research Computing and Analytics Associate, you will draw on technical knowledge and interpersonal skills to facilitate and accelerate academic research at Stanford GSB. You will collaborate with researchers, faculty, students, and staff to identify and develop innovative technical solutions to resolve research questions, and you will deliver learning opportunities and training resources to GSB researchers. Responsibilities Collaborate with faculty and researchers to understand research goals and help identify technical obstacles and solutions. Work with outside vendors to ensure secure and timely transfer of research data. Understand data types collected and how to integrate research workflows across databases and data warehouses. Research and suggest new toolsets/methods to improve data ingestion, storage, processing, and access. Contribute to guidelines, standards, and processes to ensure security of systems and data appropriate to risk. Monitor ETL processes, perform system audits, and proactively fix issues; support system performance. Serve as technical interface with software vendors and data providers to ensure researchers have effective data access in selected systems. Contribute to technical strategies and architectures to achieve research goals, using external vendors as needed. Participate in R&D to enhance the team’s capabilities, including tutorials, testing new data collection methods, and staying current with literature. Develop and deliver documentation and training for faculty and research staff. Minimum Requirements This role may be classified as either Associate or Senior Associate based on the applicant’s education and experience. Human Resources will determine the appropriate level. Desired Skills for the Associate Bachelor’s degree and a minimum of five years of relevant experience in computer science or engineering, or equivalent. Knowledge of data transfer, data warehousing, data storage technologies, and ETL for large datasets. Ability to support custom ETL, auditing, and scheduling programs. Experience with research software (R, Stata, Matlab, SAS, Julia, JavaScript). Experience with data processing at scale and understanding which tools to use when. Knowledge of relational databases and SQL. Ability to design and deploy scalable data ETL pipelines with existing and emerging technologies. Strong problem-solving, interpersonal, and communication skills. Experience in a research or academic setting (minimum 1 year). Additional Desired Skills for the Associate Bachelor's or Master’s in computer science, data science, statistics, or related field (Master’s preferred). Strong Python programming skills. Experience with large data transfers and ETL projects (Globus, rclone, SFTP); data warehouses. Knowledge of data security (deidentification, ACLs, IRB, etc.). Experience on interactive Linux and cloud platforms (AWS, BigQuery); familiarity with high-performance languages. Commitment to continual learning and professional growth; ability to work independently in a fast-paced environment. Senior Associate Additional Requirements Bachelor’s degree and at least seven years of relevant experience; Master’s preferred. Advanced data science and machine learning experience; familiarity with R, Stata, Matlab, SAS, Julia, JavaScript. Experience with data processing at scale and select appropriate tools; familiarity with text and image processing (OCR, NLP, regex, image classification). Ability to develop and deploy full-stack applications and API integrations for a research setting. Excellent problem-solving, interpersonal, and communication skills; continuous learner; service-oriented. Minimum three years in a research or academic setting applying data science and ML techniques. Compensation and Work Arrangement The expected pay range for this position is $111,142–$140,000 per year for the Associate and $145,282–$155,000 per year for the Senior Associate. This position is open to a hybrid work arrangement requiring on-site presence eight days per month, with on-site requirements during events. Stanford University pay ranges are a good faith estimate. Final pay is determined based on scope, qualifications, departmental budget, internal equity, location, and market data. The Cardinal at Work benefits program applies; specifics discussed during hiring. How to Apply Apply for this position by clicking the “Apply for Job” button. Please submit a cover letter and résumé along with your online application. EEO and Other Information Schedule: Full-time Job Code: 4777 Employee Status: Regular Grade: K Requisition ID: 105532 Work Arrangement: Hybrid Eligible
#J-18808-Ljbffr