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Overnight Remote Data Analyst Jobs in Connecticut

Sr. Engineer, Data & Analytics

Stamford, CT ยท Remote

$122K - $146K/yr

About the Role As our Sr. Engineer, Data & Analytics, you will build both the data foundation and ... This position is remote and will report into Lovesac Corporate HUB based in Stamford, CT.

Medical Economics Analyst

Hartford, CT ยท Remote

$54K - $145K/yr

We are seeking professionals with expertise in either Data Analytics or Data Strategy to help ... through data-driven decision making. Please note: This remote position is not eligible for ...

Over 300 leading healthcare organizations have come to rely on MedInsight analytic solutions for ... This position is fully remote, while occasional travel may be required. Primary Responsibilities:

The Category Analyst supports U.S. category development initiatives through data analysis ... Data integrity across customer reporting #LI-remote BIC World is an Equal Opportunity Employer. We ...

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Overnight Remote Data Analyst information

What does an overnight remote data analyst do?

An Overnight Remote Data Analyst is responsible for analyzing and interpreting data during nighttime hours, typically outside of regular business hours. This role involves collecting, cleaning, and processing data, generating reports, and providing insights to help organizations make data-driven decisions. Working remotely allows analysts to perform these tasks from anywhere, enabling companies to have 24/7 data coverage and faster turnaround on data projects. Key responsibilities may also include monitoring data pipelines, troubleshooting issues, and ensuring data quality throughout the night.

What are the key skills and qualifications needed to thrive as an overnight remote data analyst?

To thrive as an Overnight Remote Data Analyst, you need strong analytical skills, proficiency in statistical methods, and a relevant degree such as in data science, mathematics, or a related field. Familiarity with data analysis tools like SQL, Python, Excel, and visualization platforms such as Tableau, along with experience using remote collaboration systems, is typically required. Attention to detail, self-motivation, and effective written communication are crucial soft skills for succeeding in an independent, asynchronous work environment. These abilities ensure accurate data-driven insights, timely reporting, and reliable collaboration across global teams.

What are the unique challenges faced by overnight remote data analysts, and how can they effectively manage their workload and communication with daytime teams?

Overnight remote data analysts often work with limited real-time supervision and may encounter challenges such as delayed feedback, asynchronous communication, and adjusting to different time zones. To manage these challenges, it's important to establish clear handover procedures, use collaborative tools for documentation, and proactively communicate progress and roadblocks to daytime colleagues. Many organizations also encourage regular check-ins or scheduled overlap hours to ensure alignment and maintain team cohesion. Embracing these practices helps overnight analysts stay connected and productive, despite working non-traditional hours.

What is the difference between Overnight Remote Data Analyst vs Night Shift Data Analyst?

AspectOvernight Remote Data AnalystNight Shift Data Analyst
Work EnvironmentRemote, working overnight hoursOn-site or remote, working overnight hours
CredentialsTypically requires a degree in data analysis, statistics, or related fieldSimilar credentials, often with experience in data tools
Employer & IndustryTech, finance, healthcare companies with 24/7 operationsManufacturing, customer service, or healthcare sectors with night shifts

The main difference is that the Overnight Remote Data Analyst works exclusively from home during overnight hours, while the Night Shift Data Analyst may work on-site or remotely during night shifts. Both roles require similar skills and credentials, but their work environments and industry applications can differ.

What are the most commonly searched types of Remote Data Analyst jobs in Connecticut?

The most popular types of Remote Data Analyst jobs in Connecticut are:

What are popular job titles related to Overnight Remote Data Analyst jobs in Connecticut?

For Overnight Remote Data Analyst jobs in Connecticut, the most frequently searched job titles are:

Infographic showing various Overnight Remote Data Analyst job openings in Connecticut as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% Remote job distribution.

Technical Clinical Data Manager /Data Analyst (Remote)

Fairfield, CT โ€ข Remote

Penfield Search Partners
Recruiting and Staffing Servicesย โ€ขย 11 - 50 employees

Full-time

Posted 24 days ago


Job description

Contact: Neisha Camacho/Terra Parsons -
No 3rd party candidates

We are partnering with a growing biotech organization seeking a Clinical Data Manager/Data Analyst to support ongoing and upcoming clinical programs across multiple therapeutic areas.

This role will sit within a highly collaborative clinical development team and is ideal for a hands-on, analytical Clinical Data Manager who enjoys digging into the data, identifying trends or issues proactively, and developing creative solutions to improve data quality and study execution. The client is seeking someone resourceful and technically curious — not just process-oriented — with the ability to independently explore datasets, generate meaningful reports, and surface potential issues early.

The ideal candidate will bring a blend of traditional clinical data management expertise along with strong data review, querying, and analytical skills. Experience with R, SQL, SAS, or other data interrogation and reporting tools is highly desirable.

Key Responsibilities

  • Support clinical data management activities across studies from start-up through database lock
  • Perform hands-on data review and exploratory analysis to identify data trends, inconsistencies, missing data patterns, and potential study risks
  • Develop custom reports, listings, and data visualizations to support proactive data cleaning and study oversight
  • Utilize R, SQL, SAS, or similar tools to query, analyze, and troubleshoot clinical datasets
  • Partner with CROs and vendors to ensure high-quality, timely data delivery
  • Collaborate cross-functionally with Clinical Operations, Biostatistics, Statistical Programming, Medical, and Safety teams on data review strategies and issue resolution
  • Contribute to development and review of key deliverables including:
    • Data Management Plans (DMPs)
    • eCRF design and completion guidelines
    • Edit checks and query logic
    • User Acceptance Testing (UAT)
    • Data review plans and cleaning processes
  • Support ongoing query management and ensure data integrity, consistency, and inspection readiness
  • Assist with implementation of data standards, reporting enhancements, and process improvements
  • Work independently to investigate data anomalies and recommend practical solutions in a fast-paced biotech environment

Qualifications

  • BS in a scientific, technical, or clinical discipline
  • Approximately 5–8 years of clinical data management experience within biotech, pharma, or CRO environments
  • Strong hands-on experience reviewing and interrogating clinical trial data
  • Experience using R, SQL, SAS, or other querying/reporting tools to analyze clinical data and generate custom reports
  • Experience with EDC systems such as Medidata Rave, Oracle, or Veeva
  • Working knowledge of CDISC standards (SDTM/ADaM) and downstream data usage
  • Experience supporting Phase II and/or III clinical trials; CNS experience is a plus
  • Exposure to CRO/vendor oversight
  • Understanding of clinical data structures and dictionaries including MedDRA and WHODrug
  • Strong critical thinking and problem-solving skills with the ability to work independently
  • Resourceful, proactive, detail-oriented, and comfortable operating in a dynamic biotech environment
  • Strong communication and cross-functional collaboration skills