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Senior Data Analyst, AdTech, Python, Media Data Operations
Location
United States
Posted
86 days ago
Salary
0
Seniority
Senior
Job Description
Senior Data Analyst, AdTech, Python, Media Data Operations
Guideline
• Data Cleaning, Parsing & Standardization (Core Function) • 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. • Data Quality & Operational Support • 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. • Dimensional Enrichment, Modeling & Data Derivation • 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. • Analysis & Internal Stakeholder Support • 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.
Job Requirements
- 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
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