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Medal · 3 months ago

Senior/Lead Data Analyst

New York City

Full-time

Onsite

Senior Level, Lead/Staff

$150K/yr - $300K/yr

5+ years exp

Medal is a company redefining how gamers connect and share their in-game moments. They are seeking a Senior/Lead Data Analyst to ensure the quality of video data for machine learning features by partnering with various teams to enhance the accuracy and reliability of video datasets.

GamingOnline GamesVideo GamesVideo Streaming

Responsibilities

Own the video data quality program: define quality KPIs (coverage, precision/recall, calibration, temporal alignment, label latency, drift) and build dashboards that make them visible company-wide

Audit datasets at scale using SQL and Python: create automated checks for codec/bitrate/fps/resolution, audio/video sync, corruption, duplicates, and long-tail coverage by game, device, and region

Design ground-truth pipelines: human-in-the-loop reviews and labeling guidelines; measure annotator agreement, and iterate to improve label quality

Diagnose model-data issues: collaborate with ML to localize failure modes, quantify data gaps, and prioritize data collection or relabeling to move accuracy on real user content

Detect bias and drift across games, platforms, and cohorts; propose mitigations and monitor post-launch

Instrument product and ingestion to capture the metadata ML needs (e.g., encoding, device, frame rate, content type) while respecting privacy and safety constraints

Run experiments: design and analyze A/Bs and holdouts to connect data quality improvements to model and product outcomes

Champion best practices in data contracts, validation, reproducibility, and documentation; mentor analysts and influence data quality culture

Work on-site at our NYC office 5 days a week

Qualification

SQLPythonData validationA/B testingBigQueryLookerETL experienceProduct senseGaming passionCommunication

Required

5+ years in data analytics or data science with a focus on media or ML data quality in production systems

Fluency in SQL and Python (Pandas/NumPy); you're comfortable building reproducible notebooks and code-reviewed pipelines

Strong measurement chops: you've defined and computed label & model quality metrics (precision/recall/F1, mAP, AUROC, calibration, temporal IoU) and can explain their trade-offs

Data validation & ETL experience: Great Expectations/TFDV (or equivalent), dbt, and an orchestrator (Airflow/Prefect)

Warehouse & BI: BigQuery (or similar) plus Looker/Mode/Tableau (or similar); you build clear dashboards and know when to run deep dives

Experimentation: A/B testing design and analysis; comfort with pitfalls and guardrails

Product sense & communication: you turn ambiguous problems into measurable roadmaps and communicate findings clearly to technical and non-technical partners

A love for gaming, however you define it

Preferred

Experience running annotation programs (Label Studio, CVAT, Scale or custom tooling) and crafting labeling taxonomies for actions/events/scenes

Hands-on with video tooling: ffmpeg/ffprobe for metadata & probes; familiarity with OpenCV (and running lightweight inference with PyTorch/TensorFlow for scoring/spot checks)

Duplicate/near-duplicate detection (perceptual hashing, embeddings/FAISS/Milvus) and dataset dedup at scales

Privacy, safety, and policy considerations for user-generated video (GDPR/COPPA basics, PII redaction, content safety heuristics)

Spark/PySpark or distributed compute for heavy lifts

Familiarity with CV/ASR signals (scene boundary, keypoint/action recognition, speech-to-text) to enrich labels and audits

Prior history as a Medal user—share a clip or your profile!