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M Science Verified
Financial Services, Market Research, Data Analytics

Data Analyst

United StatesHybridFull TimeEntry-level (exp-based)$75,000–$100,000 /yrPosted 2 months agoVisa sponsorship available

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Role summary

M Science is seeking a detail-oriented Data Analyst to structure and enrich data through tagging and categorization. This role involves developing and maintaining tagging taxonomies for large-scale datasets, ensuring accuracy and consistency to power downstream analytics and client-facing products. The analyst will perform quality assurance, analyze metrics, and collaborate with data engineering, product, and research teams to refine methodologies and drive data quality. Responsibilities include establishing tagging standards, integrating logic into automated pipelines, and documenting guidelines. The ideal candidate has 1-4 years of experience in data analysis or data quality roles, proficiency in SQL and Python, and a strong commitment to data accuracy.

Title:
Data Analyst

Location:
New York, NY or Salt Lake City, UT

About M Science:

M Science is a data-driven research and analytics firm, uncovering new insights for leading financial institutions and corporations. We come to work every day to create actionable insights from alternative data. M Science is revolutionizing research, discovering new data sets and pioneering methodologies to provide actionable intelligence. Our research teams have decades of experience working with massive amounts of unstructured data in near real-time to discern critical insights that help clients make smarter, more informed decisions. We combine the best of finance, data and technology to create a truly unique value proposition for both financial services firms and major corporations.

Job Overview:

We're looking for a detail-oriented Data Analyst who is passionate about structuring and enriching data through tagging and categorization; who thrives on turning unstructured information into well-organized, high-quality datasets; and who is committed to the continuous improvement of our data products. In this role, you will develop and maintain tagging taxonomies applied across large-scale datasets, ensuring accuracy and consistency that directly powers downstream analytics, research, and client-facing products. You will partner closely with data engineering, product, and research teams to refine tagging methodologies and drive data quality.

Specifically, you will establish tagging standards, perform quality analysis on tagged datasets, and collaborate with stakeholders to ensure tagged data meets the needs of analytics, reporting, and machine learning initiatives.

Responsibilities:

  • Develop, maintain, and improve tagging taxonomies and classification schemas used to categorize large-scale datasets
  • Apply tags and labels to raw and semi-structured data, ensuring consistency, accuracy, and completeness
  • Perform quality assurance reviews on tagged data to identify misclassifications, gaps, and anomalies
  • Analyze tagging coverage and accuracy metrics, producing regular reports and recommendations for improvement
  • Collaborate with data engineering teams to integrate tagging logic into automated pipelines and workflows
  • Partner with research analysts and product managers to understand evolving tagging requirements and translate them into actionable specifications
  • Document tagging guidelines, rules, and decision frameworks to ensure reproducibility and scalability
  • Identify opportunities to automate or semi-automate tagging processes through rule-based or algorithmic approaches
  • Contribute to cross-functional projects related to data quality, standardization, and enrichment
  • Mentor team members on tagging best practices and provide/receive actionable feedback

Skills:

- Strong proficiency in
SQL
for querying, validating, and analyzing datasets
- Working knowledge of
Python
for data manipulation and analysis (pandas, etc.)
- Experience developing or working with classification taxonomies, tagging schemas, or labeling frameworks
- Excellent attention to detail with a strong commitment to data accuracy and consistency
- Strong analytical and problem-solving skills with the ability to identify patterns and anomalies in data
- Intellectual curiosity to understand the “why” behind the data
- Effective communication skills to articulate tagging methodologies, findings, and recommendations to both technical and non-technical stakeholders
- Ability to thrive in a culture of quality and personal accountability

Qualifications:

  • 1–4 years of experience in a data analyst, data tagging, data categorization, or similar data quality role
  • Bachelor's or higher degree, or significant experience in Statistics, Mathematics, Computer Science, Information Science, or a similar quantitative discipline

Preferred Qualifications:

  • Experience working with alternative data, large datasets, or cloud data platforms (Snowflake, Databricks, AWS)
  • Familiarity with statistical modeling, forecasting, or time-series analysis
  • Familiarity with software development workflows (e.g., version control, code reviews)

Salary Range:
$75,000-$100,000 USD/Annual

The salary offered will take into consideration an individual’s experience level and qualifications. In addition to salary, M Science offers, for eligible employees, an annual discretionary incentive bonus, competitive employee benefits, including: medical, dental & vision coverage; 401(k); life, accident, disability insurance; and wellness programs. M Science also offers paid time off packages that include planned time off (vacation), unplanned time off (sick leave), paid holidays and paid parental leave.

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