Senior Data Scientist
Tasks
- Apply graph analytics
- Conduct exploratory data analysis
- Document data readiness and modeling decisions
- Ensure reproducibility with version control and parameterized pipelines
- Evaluate model rigor with confidence intervals
- Extract relationships from unstructured text
- Implement anomaly detection
- Lead end to end data science experiments
- Perform probabilistic entity resolution
- Run LLM based named entity recognition
- Train graph neural networks
- Train interpretable classifiers
- Wrangle messy data and recommend data sources
Perks/Benefits
- 401k employer contribution
- Bereavement leave
- Company laptop
- Flexible work hours
- HSA and FSA
- Jury duty leave
- Life and disability insurance
- Medical/Dental/Vision insurance
- Paid federal holidays
- Paid leave
- Paid paternity and maternity leave
- Paid sick leave
- Professional development funding
- Referral bonus
- Remote work opportunities
- Technical supplies and equipment budget
Skills/Tech-stack
Anomaly Detection | AutoEncoder | Betweenness centrality | Boosted Trees | Cluster detection | DGL | Dedupe | Eigenvector centrality | Entity Resolution | Entity recognition | FEBRL | Feature importance | Fellegi-Sunter | Fuzzy Matching | GAT | Gradient Boosted Trees | Graph Machine Learning | Graph Neural Networks | Graph-tool | GraphSAGE | Hypothesis Testing | IGraph | Isolation Forest | LLM | Leiden algorithm | Link prediction | Logistic Regression | Machine Learning | Magellan | Motif analysis | Name transliteration | Named Entity Recognition | NetworkX | Neural Networks | NumPy | Pandas | Partial Dependence | Partial Dependence Plots | Positive unlabeled learning | Power analysis | Probabilistic record linkage | PyTorch Geometric | Python | Record Linkage | Relationship Extraction | SHAP | Scikit-learn | Senzing | Statistical Hypothesis Testing | Temporal cluster detection
Education
N/A
Roles
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