Data Scientist I

DataJobs; Scottsdale (AZ); On-site; USD 90,000 - 120,000; Full time

Job summary

Early Warning Services is seeking a Data Scientist I to drive end-to-end machine learning and AI initiatives, from problem understanding to deployment and ongoing monitoring.

You will work with senior leaders to understand business problems, aggregate data, build and validate models, and quantify model value through simulations using real-world inputs.

Qualifications

• Bachelor’s degree or equivalent in a related field.
• Minimum 2 years in data science or related work (internships or course experience allowed with a Bachelor’s degree); Master’s with internship also acceptable.
• Ability to write model development technical documents.
• Experience using data visualization tools.

Responsibilities

• Produce standard and ad hoc analytic reports.
• Assist with developing, testing, and documenting open-source code for data analysis and modeling.
• Perform data analysis tasks, including data transformations, interpreting results, and investigating root causes.
• Support model validation procedures within the Model Risk Management program.
• Independently explore and aggregate data to identify data anomalies impacting performance.
• Deliver end-to-end feature engineering, including brainstorming and validating features.
• Write production-level code in a fast-paced environment.
• Apply ML techniques to business problems to determine optimal approaches.
• Partner with Product and Engineering teams to solve problems and identify trends.
• Partner with Sales and Product teams to support customer value tests.
• Explain and visualize results for non-technical audiences.
• Maintain data integrity and confidentiality.

Skills

Data science

Data visualization

Technical writing

Education

Bachelor’s degree in Engineering, Mathematics, Statistics, Computer Science, OR related field

Master’s degree (with internship or some experience)

Job description

Early Warning Services is hiring a Data Scientist I to support end-to-end machine learning and artificial intelligence work, from business problem understanding through model deployment and ongoing monitoring. The role operates in collaboration with senior technical and business leaders.

Role Overview

This position serves as a data science team member delivering machine learning and AI concepts start to finish. Responsibilities include understanding the business problem, aggregating and exploring data, building and validating algorithms, and quantifying model value for Early Warning Customers through simulations using real world inputs. The role also includes articulating model risks, deploying completed models to support business results, and regularly measuring model accuracy, drift, and performance.

Key Responsibilities

• Produce standard and ad hoc analytic reports.
• Assist with developing, testing, and documenting open-source code for data analysis and modeling.
• Perform data analysis tasks, including programming data transformations, interpreting results, and investigating root causes.
• Contribute to Internal model validation procedures, support external Model Validations, and perform regular model validation as part of the Model Risk Management program.
• Independently explore and aggregate data to identify data anomalies that impact algorithm performance.
• Deliver end-to-end feature engineering, including brainstorming, creating, validating, and down-selecting features.
• Write production-level code in a dynamic, fast-paced environment.
• Apply a variety of machine learning techniques to business problems to arrive at an optimal approach.
• Partner with Product and Engineering teams to solve problems and identify trends and opportunities.
• Partner with Sales and Product teams to perform Customer Value tests supporting business development efforts for current and future models.
• Explain and visualize results and algorithm performance for non-technical audiences.
• Support the company commitment to protect the integrity and confidentiality of systems and data.

Required Qualifications

• Bachelor’s degree in Engineering, Mathematics, Statistics, Computer Science, Operational Research, or a related field, or equivalent work experience.
• Minimum 2 years of data science, engineering, mathematics, or related work, including internships or course experience (with a Bachelor’s degree); also acceptable is a Master’s degree without experience (or some internship).
• Ability to write model development technical documents.
• Willingness to troubleshoot system or data issues that hinder analytics environment functionality.
• Experience using data visualization tools.