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[Remote] Senior Data Analyst (AdTech | Python | Media Data Operations)

Work from home Full-time role Hiring

Note: The job is a remote job and is open to candidates in USA. Guideline.ai is a company focused on redefining the future of advertising through data transparency and advanced tools. They are seeking a Senior Data Analyst to clean, standardize, and enrich large advertising datasets while applying statistical and machine learning techniques to forecast trends and classify unstructured data.

Responsibilities

  • Build Python (Pandas/Regex) workflows to extract structure from free-form Prisma text fields containing placements, publishers, formats, devices, tactics, etc
  • Develop rule-based and pattern-based logic to recognize abbreviation variations, naming inconsistencies, and agency-specific formatting habits
  • Create normalization scripts that standardize publisher names, platform types, channels, and other key taxonomies
  • Maintain “classification dictionaries” and pattern libraries that improve accuracy over time
  • Profile incoming agency data to identify common quality issues and propose concrete remediation
  • Design QA checks to detect missing fields, malformed entries, inconsistent dimensional labels, and mismatched spend totals
  • Partner closely with Data Engineering to embed your logic into scheduled pipelines
  • Own recurring operational workflows that support data ingestion, aggregation, and quality monitoring
  • Build and maintain predictive models to support media spend forecasting, pricing analysis, and text classification for data tagging and enrichment
  • Apply statistical modeling or regression techniques to impute missing values or infer incomplete spend or performance metrics
  • Derive new fields—such as format groupings, platform classifications, creative types, and targeting attributes—using pattern recognition and model-based inference across text fields
  • Produce structured dimensions from unstructured data to improve downstream reporting
  • Document the logic and assumptions behind model-driven derivations to ensure transparency and reproducibility
  • Investigate anomalies, unexpected trends, and data gaps by tracing issues back to source fields
  • Build dashboards that help internal teams observe data quality, volume, deviations, and model-driven insights
  • Provide ad-hoc deep dives into digital spend patterns, forecast accuracy, and classification performance for product, ops, and leadership Skills
  • 5+ years of experience as a Data Analyst or Data Operations Analyst
  • Expert-level Python (Pandas, Regex) and SQL
  • Experience extracting meaning from unstructured or text-heavy data
  • Working knowledge of forecasting, regression, and basic statistical modeling (e.g., ARIMA, Prophet, linear regression, or similar methods)
  • Familiarity with text classification / NLP workflows (e.g., scikit-learn, spaCy, Hugging Face)
  • Awareness of AI-assisted development tools and basic understanding of generative AI / LLM concepts and their applications in data enrichment and automation
  • Strong understanding of data hygiene, classification logic, and dimensional modeling
  • Comfortable working in data warehouses (Snowflake, Redshift, etc.)
  • Ability to create repeatable, documented transformation logic Benefits
  • Medical, Dental, Vision, Health Savings Account, Flexible Spending Account
  • STD, Life, LTD and AD&D
  • 401(k) with a company match program
  • Unlimited Paid Time Off (PTO)
  • Paid Parental Leave
  • Commuter Benefits
  • Employee Recognition Program
  • Referral Bonus Program Company Overview
  • At Guideline, we're defining the future of how the world buys and sells media. It was founded in 2020, and is headquartered in New York, New York, USA, with a workforce of 51-200 employees. Its website is Company H1B Sponsorship
  • Guideline has a track record of offering H1B sponsorships, with 8 in 2025, 3 in 2024, 11 in 2023, 13 in 2022, 10 in 2021, 1 in 2020. Please note that this does not guarantee sponsorship for this specific role. Apply tot his job

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