Senior Data Scientist - Applied Machine Learning
Remote
3-6+ Months
Hands-on senior technical resource on a two-person KCS project team focused on developing an ML solution for identifying high-value Cisco Learning engagement opportunities.
Required Skills
Machine Learning / Statistics
Traditional predictive ML
- Statistical modeling
- Classification / probability-based modeling
- Feature engineering and feature selection
- Feature importance / ablation analysis
- Model evaluation and calibration
- Class-imbalance techniques
- Holdout and temporal validation
- Leakage identification and prevention
- Logistic Regression
- Gradient Boosted Trees, including XGBoost/LightGBM
- Scikit-learn or comparable ML framework
Traditional ML, feature engineering, statistical modeling, classification/probability analysis, class imbalance, and seasonality as key areas of need.
Languages / Data
Advanced Python
- SQL
- Pandas
- NumPy
- Relational/database analysis
- Structured + unstructured data
ML Lifecycle
ML training/evaluation workflows
- Feature-engineering pipelines
- Model monitoring
- Model registries/versioning
- Experiment tracking
- Automated testing/retraining concepts
- Production-oriented ML practices
The operating model states that Kforce work will include understanding existing signals, building experiments against individual data sources, determining associated features/dimensions, and designing/proposing feature-engineering ML stages. Deep ML expertise is mandatory.
Preferred Skills
Sales-domain feature engineering / predictive analytics
- Propensity modeling / opportunity or lead scoring
- Revenue-oriented predictive analytics
- Customer adoption, consumption, or renewal modeling
- Survival / time-to-event analysis
- NLP / text analytics
- MLflow
- Feature Store concepts
- Cloud ML ecosystem exposure
- Enterprise data and governance
- Prior Cisco experience
Important recruiter emphasis: Sales-domain ML/feature-engineering experience should be treated as especially important. Client Stakeholder explicitly wrote that Experience and Expertise in ML, Feature Engineering in Sales Domain is must.
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