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Job Location: New York, NY
Job Detail:
About Us
Since 1977 we have delivered first class solutions to insurers worldwide, by combining global reach with local decision making. We have built customer & broker relationships on years of trust, experience and execution. Through our people, our products and our partnerships, we deliver the capacity and expertise necessary to contribute to the sustainable growth of prosperous communities worldwide. To do so, our colleagues work with:
Integrity Work honestly, to enhance TransRe’s reputation
Respect Value all colleagues. Collaborate actively.
Performance We reward excellence. Be accountable, manage risk and deliver TransRe’s strengths
Entrepreneurship Seize opportunities. Innovate for and with customers.
Customer Focus Anticipate their priorities. Exceed their expectations.
We have the following job opportunity in our New York, New York office:
Description
This role will be part of our Applied Data Team and will be responsible for providing Machine Learning Engineering support. Tasks & responsibilities required of this role include but are not limited to:
- Construct machine learning models including data collection, normalization, and standardization, data pipeline construction, model selection and hyperparameter tuning, working ml systems that can add new data into ml model.
- Create apps to present ml models and host them in the cloud or locally.
- Create pipelines to query and retrieve and update data for existing applications to keep them updated
- Supervise the scaling and management of the machine learning modeling ecosystem
- Find orthogonal data sets to supplement models and increase alpha
- Stay abreast of new technology and machine learning methodologies and implement them into the model building architecture
- Work alongside (re)insurance domain experts to improve predictive aspects of their lines of business
Requirements:
- 3+ years of demonstrative excellence in building, scaling, and productizing machine learning models
- Experience working with sparse, high dimensional, and time series data
- Python ml stack
- Experience dealing with imbalanced classes
- Deep Learning Architectures
- ML Optimization Techniques
- Cloud Services: Azure, AWS, Google Cloud
- Distributed systems: Hadoop, MapReduce, Spark
- Databricks
- Ensemble Stacking and Meta Learners
- Classification and Regression Metrics
- Regularization Methods
- Version Control
- Quant trading experience welcome but not required
- Kaggle ranking of expert or higher a plus
We are an Equal Opportunity Employer (EOE) and we support diversity in the workforce.
Job Type: Full-time
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