Research & Methodology Analyst (Remote)

AI overview

The role is pivotal in ensuring the quality of scoring systems for product rankings through data analysis, documentation, and cross-functional collaboration.

The Research & Methodology Analyst will play a key role in developing, maintaining, and assuring the quality of our scoring systems that assess and rank consumer and small business products and services. The primary focus of this role is on data analysis, methodology documentation, and quality assurance of ranking models. While there is a supportive aspect of user experience research—including limited survey administration—this position emphasizes rigorous data synthesis and scoring model enhancement to drive actionable insights.

 

Responsibilities:

  • Data Analysis & Ranking Inputs

    • Collaborate with SEO, Editorial, and Data teams to collect, organize, and analyze inputs that feed into our ranking systems
    • Evaluate quantitative and qualitative data to generate actionable insights that inform our product and service rankings.
    • Utilize statistical tools and data visualization techniques to effectively communicate findings and support decision-making.
  • Scoring Model Quality Assurance & Methodology Enhancement

    • Play a central role in the quality assurance process for scoring models, ensuring that ranking outputs accurately reflect consumer and market data.
    • Identify discrepancies and recommend improvements to scoring algorithms and overall ranking logic.
    • Test and validate updates to models and methodologies prior to implementation to maintain consistency and accuracy.
  • Documentation & Process Refinement
     

    • Draft, update, and refine detailed documentation that explains methodology, scoring logic, and ranking processes.
    • Develop clear, user-friendly guides and reports that translate complex data insights into practical recommendations.
    • Continuously evaluate and refine internal processes to enhance efficiency in data analysis and ranking model performance.
       
  • Cross-functional Collaboration & Continuous Improvement

    • Engage with various internal teams to integrate new data sources and market trends into our assessment models.
    • Keep abreast of industry trends in methodology and data analytics to drive continuous improvement in our ranking approaches.
    • Provide periodic updates and presentations to internal stakeholders outlining key insights and methodological adjustments.

 

Qualifications & Experience: 

  • Bachelor’s degree in Computer Science, Mathematics, Statistics, or a related field preferred
  • Minimum of 2 years' experience in data analysis, methodology development, or quality assurance preferred.
  • Experience in integrating data from multiple sources to inform ranking systems or similar decision-making models is preferred
  • Prior exposure to user research is beneficial but not a primary requirement.
  • Experience working as part of a multidisciplinary team.
  • Ability to translate complex quantitative data and methodological details into actionable insights.

Technical Skills:

  • Competence in data visualization and creating comprehensive analytical reports 
  • Proficiency with spreedsheets (Excel/Sheets) including pivots, lookups, array formulas; comfort auditing large, messy datasets 
  • A strong analytical mindset with meticulous attention to detail 

 

Benefits: 

  • Competitive salary
  • Medical, dental and vision coverage 
  • 35 Days of PTO (Including Bank Holidays)
  • Every third Friday of the month off
  • Disability coverage 
  • Employee assistance program 
  • Paid parental leave program 

Forbes Advisor provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.

#LI-REMOTE #LI-NM1

Perks & Benefits Extracted with AI

  • Other Benefit: Disability coverage
  • Paid Parental Leave: Paid parental leave program
  • Paid Time Off: 35 Days of PTO (Including Bank Holidays)

Forbes Advisor is looking for a Data Research Engineer - Data Extraction to join the Forbes Marketplace Performance Marketing team with a focus on supporting one of Forbes business verticals. If you're looking for challenges and opportunities similar to those of a start-up, with the benefits of an established, successful company read on.We are an experienced team of industry experts dedicated to helping readers make smart decisions and choose the right products with ease. Marketplace boasts decades of experience across dozens of geographies and teams, including Content, SEO, Business Intelligence, Finance, HR, Marketing, Production, Technology and Sales. The team brings rich industry knowledge to Marketplace’s global coverage of consumer credit, debt, health, home improvement, banking, investing, credit cards, small business, education, insurance, loans, real estate and travel.The Data Extraction Team is a brand new team who plays a crucial role in our organization by designing, implementing, and overseeing advanced web scraping frameworks. Their core function involves creating and refining tools and methodologies to efficiently gather precise and meaningful data from a diverse range of digital platforms. Additionally, this team is tasked with constructing robust data pipelines and implementing Extract, Transform, Load (ETL) processes. These processes are essential for seamlessly transferring the harvested data into our data storage systems, ensuring its ready availability for analysis and utilization.A typical day in the life of a Data Research Engineer will involve acquiring and integrating data from various sources, developing and maintaining data processing workflows, and ensuring data quality and reliability. They collaborate with the team to identify effective data acquisition strategies and develop Python scripts for data extraction, transformation, and loading processes. They also contribute to data validation, cleansing, and quality checks. The Data Research Engineer stays updated with emerging data engineering technologies and best practices. 

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