Job Role: Data Scientist
Job Location: Burgess Hills,UK
Job Type: Contract/FTC
Additional info for data science - No mobile experience needed. Experience with Python - Streamlit, Plotly, numpy, pandas, matplotlib, seaborn and with AWS - S3 a plus. Someone who is smart and truly a data scientist.
Platform: Python/Streamlit production intelligence platform for the Amex Travel Mobile App - centralizes telemetry (Snowflake, ELF/OpenSearch, App Store Connect, Jira, etc.) into dashboards for TLS leadership. Strict 4-layer architecture: Ingestion ? Analysis ? S3 Storage ? Visualization.
Technical Skills
- Strong Python 3.11+, pandas, NumPy for data transformation and time-series work
- Streamlit dashboard development (multi-page, session state, query-param nav)
- API/SQL data integration (Snowflake, OpenSearch, REST sources)
- Visualization: plotly, matplotlib, seaborn
- AWS (boto3, S3/Parquet), Docker, Kubernetes, CI/CD
- Secrets/auth (JWT, cryptography, Proxy handling); testing with pytest
Data Science/Analytics
- Applied statistics for anomaly detection (rolling median + MAD z-score, thresholds); scipy a plus
- Time-series thinking: daily/weekly/monthly frequency-aware baselining
- Turns raw telemetry into decision-ready insights (not deep ML, but solid quantitative reasoning)
Business Knowledge
- Understands mobile app KPIs across Bookings, Adoption, Engagement, App Health, Card Member Voice, Quality Engineering
- Familiar with iOS/Android store metrics, crash/stability, QE/regression concepts
- Translates leadership questions into metrics and views
Seniority
- Senior-level ownership within an established layered architecture; respects design principles (no business logic in UI, filter-agnostic analysis)
- Contributes to and follows Architecture Decision Records (ADRs)
- Owns features end-to-end: data source ? analysis ? dashboard
Communication & Collaboration
- Communicates data-driven findings clearly to leadership and non-technical stakeholders
- Works cross-functionally with QE, delivery, and product teams
- Strong documentation habits
Go-Getter
- Self-directed in integrating new data sources and extending hubs/domains
- Curious and metric-obsessed; proactively closes visibility gaps
- Bias to ship while keeping the architecture clean
Rate:
Not specified
Location:
Burgess Hills
IR35 Status:
Not specified
Remote Status:
Not specified
Industry:
Data & Analytics
Seniority Level:
Senior