Data Research Analysis Manager (Remote)

AI overview

Lead a team conducting competitive analysis to ensure data quality and accuracy, providing essential insights for consumers' financial and insurance decisions.

We are seeking a Data Research Analysis Manager to join our team and assist our editorial team in creating top-quality content. In this role, you will lead a team that provides competitive analysis on the market and ensures the quality and accuracy of data collection and analysis for various subjects. Your team’s research and analysis will be a key component of making trustworthy, relevant assessments of products and services, and will help thousands of consumers make informed decisions related to their financial planning, insurance and entrepreneurial needs. 

If you are looking for a challenging and exciting opportunity similar to those found at a start-up, with the benefits of a seasoned and successful company, then this may be the role for you. 

Analytical Leadership 

  • Own the analytical frameworks and methodology implementation across including financial services, insurance, SaaS, home services
  • Contribute to and evolve scoring models, weighting logic, and evaluation criteria used in best-of lists and comparative analyses 
  • Design and evolve scoring models, weighting logic, and evaluation criteria used in best-of lists and comparative analyses 
  • Line manage and mentor analyst with a focus on analytical development 
  • Support analysts in tackling complex questions and ambiguity in datasets 
  • Encourage critical thinking, challenge assumptions and foster a culture of excellent 

Technical Skills:

  • Perform and review complex analysis using SQL, Python, and BI tools
  • Guide analysts on best practices in data modelling, transformation and visualisation 
  • Improve data pipelines, tooling and workflows 
  • Champion documentation of logic, assumptions and limitations 

Research Quality:

  • Define and enforce quality standards for data collection, validation, and analysis 
  • Review research outputs for methodological soundness, bias, and edge cases 
  • Lead continuous improvement of research processes, with a focus on automation, scalability, and accuracy 

About You:

  • Highly analytical, with a strong instinct for questioning data quality and methodology 
  • Comfortable working hands-on with complex datasets 
  • Able to explain technical concepts clearly to non-technical stakeholders 
  • Naturally curious, with a strong sense of ownership over research quality 
  • Confident operating in an evolving environment where not all problems are fully defined 

Qualifications and Skills 

  • Degree in a relevant field, such as Economics, Statistics, Business, or equivalent training and experience 
  • Experience in data or content research in the publishing industry, particularly on B2B or Financial topics 
  • Advanced proficiency in using Excel for data analysis and manipulation 
  • Proficiency in SQL and/or Python for data manipulation 
  • Proficiency in data visualization tools, particularly Tableau 
  • Experience designing scoring models, ranking or comparative frameworks is a plus 

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

  • Health Insurance: Medical, dental and vision coverage
  • Other Benefit: Employee assistance program
  • 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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