Location:
2727 N Central Ave, Phoenix, Arizona 85004 United States of America
As a Data Scientist, you will be responsible for evaluating and improving U-Haul’s products and services. You will be part of a multi-disciplinary team of Data Scientists, Engineers and Business Experts and will bring Big Data Analytics and scientific rigor to the team. This process involves understanding complex business, formulating new solutions, wrangling/munging structured and unstructured data, creating descriptive and predictive models. You are expected to embrace new technologies and deliver smart solutions and services, collaborate with teams, share their knowledge and collectively grow capability, skills, and knowledge in the team.
Responsibilities
Evaluating various business problem and formulating machine learning solutions to them Communicating complex technical concepts to stakeholders with confidence and integrity Designing and implementing the data science model appropriate to the business challenge (classification, regression, recommendation systems, sentiment analysis, neural network, LLM etc.) Working with business stakeholders to determine metrics for evaluating the models Design of repeatable experiments for evaluation, and developing mechanisms for monitoring these models Working with the engineering teams for deploying these models to meet the specific project requirements such as time real-time constraints Building data visualizations, reports, and presentations for varied audiences Rapidly learning and implementing new technologies and tools Handling a variety of responsibilities under pressure and functioning independently The ability to communicate and present both orally and in writing, and comfortable with ambiguity, uncertainty, and change
Qualifications
Master’s degree or Ph.D. from an accredited college/university in Computer Science, Statistics, Mathematics, Engineering, Physics or related fields, with a minimum of 3 years of relevant experience Exposure to and familiarity with a variety of statistical and machine learning techniques including but not limited to Regression and Classification, Natural Language Processing, Computer Vision, Recommender Systems, Time-Series Analysis Experience with applying and deploying computer vision models is a plus Substantial depth in one or more of the above techniques with past industry projects and/or academic research. Proven experience processing and analyzing structured and unstructured data Experience in SQL is required Experience in Python is required Experience using C#, Java, Scala and Spark are desired Experience in BI reporting tool such as PowerBI or Tableau is desired Experience in Databricks, AzureML is a plus
U-Haul Holding Company, and its family of companies including U-Haul International, Inc. (“U-Haul”), continually strives to create a culture of health and wellness. Consistent with applicable state law, U-Haul will not hire or re-hire individuals who use nicotine products. The states in which U-Haul will decline to hire nicotine users are: Alabama, Alaska, Arizona, Arkansas, Delaware, Florida, Georgia, Hawaii, Idaho, Iowa, Kansas, Maryland, Massachusetts, Michigan, Nebraska, Pennsylvania, Texas, Utah, Vermont, Virginia, and Washington. U-Haul has observed this hiring practice since February 1, 2020 as part of our commitment to a healthy work environment for our team.
U-Haul is an equal opportunity employer. All applicants for employment will be considered without regard to race, color, religion, sex, national origin, physical or mental disability, veteran status, or any other basis protected by applicable federal, provincial, state or local law. Individual accommodations are available on requests for applicants taking part in all aspects of the selection process. Information obtained during this process will only be shared on a need to know basis.
While all employers are vetted to meet the Maricopa Guidelines, the job postings are not individually reviewed. Students should be diligent in ensuring they are applying for positions that meet their needs and are not in violation of the Maricopa guidelines.