Senior Data Scientist (AIOps & MLOps) – W2 only

Senior Data Scientist — Forecasting, AI-Ops & ML-Ops

Contract Opportunity | Irving, TX

++Position Overview and Key Responsibilities++ : We’re seeking a senior Data Scientist with deep expertise in forecasting and market expansion for the hospitality (hotels) sector. You’ll build and productionize models that identify and size demand in new geographic markets , accelerate B2B/new-logo acquisition , and guide pricing, sales targeting, and inventory strategy. You’ll own the end-to-end lifecycle—from data discovery and modeling to AIOps/MLOps and clear, executive-level storytelling.

What you’ll do

• Forecasting for expansion: Design hierarchical and geospatial time-series models to predict room-night demand, RevPAR/ADR, lead volume, and conversion potential across new markets and sub-markets.
• New business acquisition modeling: Build propensity and LTV models for corporate accounts, tours, and groups; prioritize high-value segments and whitespace geographies.
• Causal & scenario analysis: Run MMM/causal inference to quantify marketing/sales lift; simulate “what-ifs” for pricing, distribution, channel mix, and opening timelines.
• Decision storytelling: Translate findings into crisp narratives and visuals for executives, development, sales, and revenue management—turn models into action.
• MLOps ownership: Productionize pipelines (data → features → model → service), implement CI/CD, versioning, model registry, and automated testing.
• AIOps & reliability: Set up monitoring, drift detection, alerting, SLA/SLOs, and incident playbooks to keep models healthy post-launch.
• Deployment strategy: Choose and execute batch/real-time/streaming deployments; run shadow, canary, blue-green releases; measure impact and rollback as needed.
• Partner cross-functionally: Work with RevOps, Sales, Marketing, Development, and Finance to align models with business targets and P&L.

Tech stack you’ll use

• Python & data: pandas, NumPy, scikit-learn, statsmodels, Prophet/darts, XGBoost/LightGBM; optional: PyTorch/TensorFlow.
• Geospatial/time series: GeoPandas, shapely, H3, raster/tiling basics; hierarchical & intermittent demand methods.
• Visualization & storytelling: Tableau (must-have), plus notebooks and executive dashboards.
• MLOps/AIOps: MLflow/Weights & Biases, feature stores, model registry; Evidently/Arize/Fiddler for monitoring; Docker, Kubernetes; Airflow/Prefect; GitHub Actions/GitLab CI.
• Data & cloud: SQL, dbt; Snowflake/BigQuery/Redshift; AWS/GCP/Azure services.

++Key Qualifications and Skillset for this Role++

Must-haves

• 5–8 years in applied data science with a focus on forecasting/time-series and market expansion ; hospitality/hotels experience strongly preferred.
• Track record deploying models to production with MLOps best practices and AIOps observability.
• Exceptional storytelling skills—turn complex analyses into simple, persuasive narratives for senior leadership.
• Advanced SQL and Python; expert with Tableau dashboards for executives and operators.
• Experience with geospatial datasets (supply, demand, comp sets, OTA/search data, mobility, macro indicators).

Nice-to-haves

• Causal inference (DiD, uplift, synthetic controls) and MMM.
• Knowledge of revenue management, distribution channels, and hotel development cycles.
• Experience with privacy-safe data partnerships and clean rooms.

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Success metrics

• Forecast accuracy (e.g., MAPE/WAPE/RMSE) at market and sub-market levels.
• Pipeline impact: qualified leads, win rate, and revenue lift in target geos.
• Time-to-production, model uptime, latency, and alert MTTR.
• Executive adoption: dashboard engagement and decision outcomes tied to model insights.