W2 Acceptable
Applied Scientist III 116467-1
Location: Seattle, WA REMOTE
Duration: 5 Months
(Possible Extension)
Number and Type of Interviews: 2- 30 min
Job Description:
We are seeking an experienced Data Science Contractor to lead the development and implementation of a new trouble ticket classification model. This role involves collaborating closely with cross-functional teams and external partners to design, test, and deploy an advanced model that meets the strategic objectives of improved accuracy and performance in automated ticket classification.
Reason for request:
Due to poor data quality and strained data science resources, a temporary, dedicated science resource is required for a short period of time to complete a ticket labeling model that aligns with AR Tech Support's needs. Investing in this temporary role will directly improve data accuracy and operational efficiency for both AR Tech Support and BADS.
Typical Tasks:
Develop a new ticket classification model using labeled, historical data
Collaborate with internal teams to define model requirements, gather data, and interpret results.
Implement a robust model testing regime to validate the effectiveness against predefined accuracy metrics.
Establish and oversee a continuous improvement strategy for the classification model, including regular data benchmarking and revision schedules.
Work closely with technical and non-technical stakeholders to ensure the model aligns with business needs and compliance standards.
Provide expertise in machine learning and predictive modeling to optimize the performance of the classification system.
Document all phases of model development and provide training and support to internal teams on utilizing the new system.
Qualifications:
* Bachelors or Master's degree in an analytically rigorous field (Data Science, Statistics, Computer Science, Industrial Engineering, Econometrics).
- Experience as an Client engineer or data scientist role building and deploying Client models on the cloud.
- Experience writing code in Python and SQL, or similar, with documentation for efficient knowledge sharing and reproducibility.
- Demonstrable track record of dealing well with ambiguity, prioritizing needs, and delivering results in a dynamic environment.
- Excellent communication skills with ability to explain complex technical concepts to non-technical audience, while also efficiently interacting with deeply technical peers.
- Knowledge of AWS (e.g. Athena, Sagemaker, S3, EC2, RDS).
Leadership Principles:
-Deliver results
- Bias for action
- insist on high standards
Top 3 must-have hard skills
Deploying Client models
Python
NLP
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