3721 Aipu jobs in Florida

Earn an upfront amount for every order you deliver, even if it's canceled by the customer

Keep 100% of your tips + earn extra with special incentives

Earn Wait Pay when you schedule your time with us (varies by market)

No restaurants, no riders - deliver from a familiar, centralized facility. That's it!

Choose your own schedule and deliver when you want

Part time work, seasonal work, temporary work

With flexible hours you can make your own schedule and drive as little, or as much as you want!

Be at least 21 years or older

Valid U. S. driver's license

Vehicle

Insurance

Registration in your name

Smartphone

Willing & able to pass a pre-paid alcohol delivery training course (where applicable)

Delivery Driver Partners must have a valid driver's license

Minimum auto insurance

Complete a background check

Their own reliable car

Data + text plan

The salary range for this position is: $143,320 - $273,930.

Employees may be eligible for pay incentives based on overall corporate and individual performance and at the discretion of the USAA Board of Directors.

Relocation assistance is available for this position.

Comprehensive medical, dental and vision plans, 401(k), pension, life insurance, parental benefits, adoption assistance, paid time off program with paid holidays plus 16 paid volunteer hours, and various wellness programs.

Our career path planning and continuing education assists employees with their professional goals.

Individuals residing within a 60-mile radius of a USAA office will be expected to work on-site 4 days per week.

Bachelor's degree in mathematics, computer science, statistics, economics, finance, actuarial sciences, science and engineering, or other similar quantitative discipline; OR 4 years of experience in statistics, mathematics, quantitative analytics, or related experience (in addition to the minimum years of experience required) may be substituted in lieu of degree.

6 years of experience in a predictive analytics or data analysis OR Advanced Degree (e.g., Master's, PhD) in mathematics, computer science, statistics, economics, finance, actuarial sciences, science and engineering, or other similar quantitative discipline and 4 years of experience in predictive analytics or data analysis.

4 years of experience in training and validating statistical, physical, machine learning, and other advanced analytics models.

4 years of experience in one or more dynamic scripted language (such as Python, R, etc.) for performing statistical analyses and/or building and scoring AI/ML models.

Proven experience writing code that is easy to follow, well documented, and commented where necessary to explain logic (high code transparency).

Strong experience in querying and preprocessing data from structured and/or unstructured databases using query languages such as SQL, HQL, NoSQL, etc.

Strong experience in working with structured, semi-structured, and unstructured data files such as delimited numeric data files, JSON/XML files, and/or text documents, images, etc.

Demonstrated skill in performing ad-hoc analytics using descriptive, diagnostic, and inferential statistics.

Ability to assess and articulate regulatory implications and expectations of distinct modeling efforts.

Advanced experience with the concepts and technologies associated with classical supervised modeling for prediction such as linear/logistic regression, discriminant analysis, support vector machines, decision trees, forest models, etc.

Advanced experience with the concepts and technologies associated with unsupervised modeling such as k-means clustering, hierarchical/agglomerative clustering, neighbors algorithms, DBSCAN, etc.

Experience guiding and mentoring junior technical staff in business interactions and model building.

Experience communicating analytical and modeling results to non-technical business partners with emphasis on business recommendations and actionable applications of results.

Prior U.S. military service or being a military spouse/domestic partner is highly valued.

3+ years in marketing analytics audience strategy, or paid media.

3+ years working with 3rd party data sources (data co-ops, data marketplaces, credit bureaus) to build marketing targeting models.

3+ years in digital platforms (Adobe, Google) and clickstream data.

3+ years in identity resolution - deterministic/probabilistic matching, household graphs, clean rooms, etc.

Expert proficiency in SQL and Python or R; comfortable in cloud data environments (Snowflake, Bigquery, Databricks).

Experience with data visualization or BI tools (Tableau, Power BI) to communicate insights effectively.