UPLAND CAPITAL GROUP INC
Data Scientist AIMLRLBayesian
UPLAND CAPITAL GROUP INC, Dallas, Texas, United States, 75215
Full time Employment Opportunity_
Primary Function: _
Our Data Science and Actuarial model environment and architecture is containerized, and we are cloud based, running on Azure. We aim to be completely automated with processes to build, provision, and deploy our models and products. Our models will range from standard AI and ML models, to RL, to Bayesian simulation models which will require creative problem solving and a close collaboration with stakeholders across the organization, not limited by a ‘one size fits all’ mindset.
Duties and Responsibilities:
Formalize business problems as technical objectives statements
Approach every problem with support from literature with an openness to discussion.
AI and Machine Learning approaches to solve new problems; not limited to vision and text problems
Bayesian simulation for parametrization and predictive models, Reinforcement Learning for scaling experiments, Natural Language Processing; including but not limited to transformers
Optimization approaches for targeting business objectives
Strong understanding of parametric modelling approaches and statistical distributions
Understand and apply model privacy and security within a structured Model Engineering process
Build full products on a fully containerized model architecture
Collaborate with stakeholders, you will report to the VP of Data Science.
Other duties assigned by management
Experience, Education, Special Skills Required:
A Master’s degree with 2-5 years experience
OR
a Bachelor’s degree with 5-8 years experience
STEM degree or related field, or equivalent experience
2-5 years of experience as a Data Scientist
Strong experience working with relational (SQL) and non-relational (NoSQL) databases End-to-end experience building, validating, and deploying AI/ML/RL/Bayes models
Strong knowledge of statistical distributions, including Bayesian mathematics
Knowledge of agile development practices using Git
Experience working with Property & Casualty product pricing or claims models
**
Bonus Skills: **
Experience with vector databases and transformer models
Aggregate and extreme value distribution modelling a positive
Hands on experience with the main cloud providers AWS/Azure/GCP
Knowledge of Linux commands and ability to work in terminal, especially server side
Experience working at a start-up or financial services
Primary Function: _
Our Data Science and Actuarial model environment and architecture is containerized, and we are cloud based, running on Azure. We aim to be completely automated with processes to build, provision, and deploy our models and products. Our models will range from standard AI and ML models, to RL, to Bayesian simulation models which will require creative problem solving and a close collaboration with stakeholders across the organization, not limited by a ‘one size fits all’ mindset.
Duties and Responsibilities:
Formalize business problems as technical objectives statements
Approach every problem with support from literature with an openness to discussion.
AI and Machine Learning approaches to solve new problems; not limited to vision and text problems
Bayesian simulation for parametrization and predictive models, Reinforcement Learning for scaling experiments, Natural Language Processing; including but not limited to transformers
Optimization approaches for targeting business objectives
Strong understanding of parametric modelling approaches and statistical distributions
Understand and apply model privacy and security within a structured Model Engineering process
Build full products on a fully containerized model architecture
Collaborate with stakeholders, you will report to the VP of Data Science.
Other duties assigned by management
Experience, Education, Special Skills Required:
A Master’s degree with 2-5 years experience
OR
a Bachelor’s degree with 5-8 years experience
STEM degree or related field, or equivalent experience
2-5 years of experience as a Data Scientist
Strong experience working with relational (SQL) and non-relational (NoSQL) databases End-to-end experience building, validating, and deploying AI/ML/RL/Bayes models
Strong knowledge of statistical distributions, including Bayesian mathematics
Knowledge of agile development practices using Git
Experience working with Property & Casualty product pricing or claims models
**
Bonus Skills: **
Experience with vector databases and transformer models
Aggregate and extreme value distribution modelling a positive
Hands on experience with the main cloud providers AWS/Azure/GCP
Knowledge of Linux commands and ability to work in terminal, especially server side
Experience working at a start-up or financial services