Über
Overall Purpose
This position serves as a data science team member in the Model Validation and Monitoring Team delivering leading edge machine learning models to our clients. This includes providing effective challenges to model development, conduct model monitoring and performance tracking, provide root cause analysis of model performance, exploring, building, validating, and deploying models.
Essential Functions Lead model monitoring activities, including tracking performance metrics, detecting model and data drift, identifying data quality issues, providing root cause analysis, and recommending remediation strategies.
Conduct rigorous model validation by providing effective challenges during model development phases, including performance testing, benchmarking, provide remediation plan, and documentation to ensure models meet business, technical, and regulatory standards.
Explore and aggregate data independently to uncover data anomalies that impact algorithm performance
Write production level code in a dynamic, start-up environment
Solve complex problems using terabyte size data sets
Apply of a variety of machine learning techniques to a business problem to arrive at optimal approach
Partner with Product and Engineering teams to solve problems and identify trends and opportunities
Explain and visualize results and algorithm performance to non-technical audiences
Support the company's commitment to protect the integrity and confidentiality of systems and data.
Minimum Qualifications Master's Degree in Mathematics, Statistics, Computer Science, Operational Research or related field;
A minimum of 2 years of data science, engineering, mathematics, or related work experience is required.
Experience developing data science pipelines & workflows in Python, R or equivalent programming language. Experience in writing and tuning SQL. Experience handling terabyte size datasets with Spark language.
Experience applying various machine learning techniques, and understanding the key parameters that affect model performance
Experience using ML libraries, such as scikit-learn, mllib, etc.
Experience using data visualization tools
Able to write production level code, which is well-written and explainable
Ability to effectively communicate findings from complex analyses to non-technical audiences.
Background and drug screen
Preferred Qualifications PhD/MSc in Mathematics, Statistics, Computer Science, Operational Research or related field; Advanced degree preferred.
Experience of using advanced ML algorithms building, testing, and deploying fraud models.
Hands-on experience with PySpark
2+ years of industry experience in building or validating machine learning models
Demonstrable track record of dealing well with ambiguity, prioritizing needs, and delivering results in a dynamic environment
Experience exploring data and finding hidden patterns and data anomalies
Physical Requirements Working conditions consist of a normal office environment. Work is primarily sedentary and requires extensive use of a computer and involves sitting for periods of approximately four hours. Work may require occasional standing, walking, kneeling, and reaching. Must be able to lift 10 pounds occasionally and/or negligible amount of force frequently. Requires visual acuity and dexterity to view, prepare, and manipulate documents and office equipment including personal computers. Requires the ability to communicate with internal and/or external customers. Employee must be able to perform essential functions and physical requirements of position with or without reasonable accommodation.
The above job description is not intended to be an all-inclusive list of duties and standards of the position. Incumbents will follow instructions and perform other related duties as assigned by their supervisor.
Early Warning Services is an equal opportunity employer.
The base pay scale for this position in: Phoenix, AZ/ Chicago, IL in USD per year is: $118,000 - $152,000. San Francisco, CA in USD per year is: $142,000 - $183,000. Additionally, candidates are eligible for a discretionary incentive plan and benefits.
This pay scale is subject to change and is not necessarily reflective of actual compensation that may be earned, nor a promise of any specific pay for any specific candidate, which is always dependent on legitimate factors considered at the time of job offer. Early Warning Services takes into consideration a variety of factors when determining a competitive salary offer, including, but not limited to, the job scope, market rates and geographic location of a position, candidate's education, experience, training, and specialized skills or certification(s) in relation to the job requirements and compared with internal equity (peers). The business actively supports and reviews wage equity to ensure that pay decisions are not based on gender, race, national origin, or any other protected classes. Early Warning Services, LLC ("Early Warning") considers for employment, hires, retains and promotes qualified candidates on the basis of ability, potential, and valid qualifications without regard to race, religious creed, religion, color, sex, sexual orientation, genetic information, gender, gender identity, gender expression, age, national origin, ancestry, citizenship, protected veteran or disability status or any factor prohibited by law, and as such affirms in policy and practice to support and promote equal employment opportunity and affirmative action, in accordance with all applicable federal, state, and municipal laws. The company also prohibits discrimination on other bases such as medical condition, marital status or any other factor that is irrelevant to the performance of our employees. Early Warning Services LLC is a proud participant in E-Verify, a federal program to help ensure a legal and authorized workforce. As part of our hiring process, we electronically verify the employment eligibility of all new hires through E-Verify. For more information on your rights and responsibilities under E-Verify please visit Home | E-Verify.
Sprachkenntnisse
- English
Hinweis für Nutzer
Dieses Stellenangebot stammt von einer Partnerplattform von TieTalent. Klicken Sie auf „Jetzt Bewerben“, um Ihre Bewerbung direkt auf deren Website einzureichen.