
Assistant Director, Data Science
- The Woodlands, TX
- Permanent
- Full-time
- Applies knowledge of sophisticated analytics techniques to manipulate large structured and unstructured data sets to generate insights to inform business decisions.
- Designs, develops and deploys Natural Language Processing (NLP) models and algorithms such as transformers, encoder and decoder models in projects.
- Follows the latest models, algorithms and trends in NLP field.
- Explores and applies Computer vision algorithms in insurance domain.
- Applies machine learning models to support risk selection and pricing decisions in insurance.
- Identifies and tests hypotheses, ensuring statistical significance, as part of building and developing predictive models for business application.
- Translates quantitative analyses and findings into accessible visuals for non-technical audiences, providing a clear view into interpreting the data.
- Documents and presents work progress, findings, and potential chances to both technical and non-technical audience.
- Enables the business to make clear trade-offs between and among choices, with a reasonable view into likely outcomes.
- Responsible for part of components of highly complex projects; Guide others as a technical consultant for the team.
- Customizes analytic solutions to specific client needs.
- Responsible for smaller components of projects of moderate-to-high complexity.
- Regularly engages with the data science community and participates in cross-functional working groups.
- Telecommuting permitted up to 100%.
- Demonstrated knowledge with deep learning modeling and programming including PyTorch and Tensorflow.
- Predictive modeling, data science techniques, machine learning models and statistical methods.
- Deep Learning techniques including deep neural networks (DNN) and their applications.
- Python and R programming through hands-on experience.
- Computer Vision modeling expertise.
- Demonstrated advanced knowledge of Natural Language Processing including CNN, RNN, LSTM, Transformers and Large language models.
- Machine Learning expertise in building models including GLM’s, Logistic Regression, Tweedie regression and XGBoost.
- Tableau and Power BI.
- MS Excel and its advanced features including Pivot tables, Lookups, Macros and MS PowerPoint.