Contact Center Data Analyst
Phoenix, AZ · On-site +1
... remote work. As a Data Analyst, team members will be responsible for evaluating and improving U ... sentiment analysis, neural network, etc.) * Communicating complex technical concepts to ...
Contact Center Data Analyst
Phoenix, AZ · On-site +1
... remote work. As a Data Analyst, team members will be responsible for evaluating and improving U ... sentiment analysis, neural network, etc.) * Communicating complex technical concepts to ...
Brand Marketing Manager
Scottsdale, AZ · On-site +1
Scottsdale, AZ (Hybrid or Remote options available) Employment Type: Full-Time Position Overview ... Analyze brand metrics (awareness, sentiment, engagement) and use insights to optimize strategies.
Brand Marketing Manager
Scottsdale, AZ · On-site +1
Scottsdale, AZ (Hybrid or Remote options available) Employment Type: Full-Time Position Overview ... Analyze brand metrics (awareness, sentiment, engagement) and use insights to optimize strategies.
Remote Sentiment Analysis information
What are some common challenges faced by professionals working in remote sentiment analysis roles, and how can they be managed?
One of the main challenges in remote sentiment analysis roles is maintaining accuracy across diverse datasets, especially when interpreting nuanced language or cultural context. Working remotely can also make collaboration with team members and quick feedback loops more difficult. To overcome these issues, professionals often use collaborative platforms for regular communication, participate in ongoing training to stay updated on language trends, and rely on standardized annotation guidelines to ensure consistency. Being proactive in seeking feedback and sharing insights with the team greatly enhances both individual and project performance.
What are the key skills and qualifications needed to thrive as a remote sentiment analyst, and why are they important?
To thrive as a Remote Sentiment Analyst, you need a background in linguistics, data analysis, and a strong understanding of natural language processing (NLP), often supported by a degree in a related field. Familiarity with sentiment analysis tools, machine learning platforms, and data visualization software is typically required. Strong attention to detail, critical thinking, and effective written communication help analysts interpret nuanced data and present findings clearly. These skills are essential for accurately assessing sentiment in large data sets and driving actionable insights for business or research objectives.
What is remote sentiment analysis?
Remote sentiment analysis is the process of evaluating and interpreting the emotional tone behind text data, such as social media posts, customer reviews, or emails, while working from a remote location. Professionals in this field use natural language processing (NLP) tools and machine learning algorithms to identify opinions, attitudes, or emotions expressed in written content. This information helps businesses understand customer feelings, improve products, and enhance marketing strategies. Remote sentiment analysts often collaborate with teams online and use cloud-based platforms to access and analyze large datasets. The role requires strong analytical skills, attention to detail, and proficiency with relevant software.
What is the difference between Remote Sentiment Analysis vs Remote Data Labeling Specialist?
| Aspect | Remote Sentiment Analysis | Remote Data Labeling Specialist |
|---|---|---|
| Required Credentials | Basic data analysis, NLP knowledge | Data annotation, labeling tools familiarity |
| Work Environment | Remote, tech companies, AI/ML projects | Remote, AI/ML, data preparation teams |
| Industry Usage | AI, NLP, customer feedback analysis | Machine learning training data creation |
| Common Search Intent | Understanding sentiment analysis roles | Comparing data labeling jobs |
Remote Sentiment Analysis involves evaluating text data to determine sentiment, often requiring NLP skills. Remote Data Labeling Specialists focus on annotating data for machine learning models, including sentiment labels. While both roles support AI development, sentiment analysis emphasizes interpreting data, whereas data labeling involves preparing data. Candidates should consider their skills and career goals when choosing between these roles.
What are popular job titles related to Remote Sentiment Analysis jobs in Arizona? For Remote Sentiment Analysis jobs in Arizona, the most frequently searched job titles are:
What job categories do people searching Remote Sentiment Analysis jobs in Arizona look for? The top searched job categories for Remote Sentiment Analysis jobs in Arizona are:
What cities in Arizona are hiring for Remote Sentiment Analysis jobs? Cities in Arizona with the most Remote Sentiment Analysis job openings:
Full-time
Medical, Dental, Vision, Life, Retirement, PTO
Re-posted 17 days ago
U-Haul rating
6.1
Based on 519 frontline employees who took The Breakroom Quiz
146th of 171 rated vehicle equipment hire
Job description
Location:
2727 N Central Ave, Phoenix, Arizona 85004 United States of AmericaThis position is not eligible for employer sponsorship.
To ensure a fair and consistent evaluation process, candidates are expected to complete all interviews and assessments independently and without the use of artificial intelligence tools (including AI-generated responses, prompts, or real-time assistance).Use of AI throughout the application and recruiting process may result in removal from consideration. Our goal is to get to know your authentic experiences, communication style, and problem-solving approach.
This position is local to our corporate campus located in Phoenix, AZ and is ineligible for fully remote work.
As a Data Analyst, team members will be responsible for evaluating and improving U-Haul's products and services. You will be interacting with multi-disciplinary teams 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 functions, creating new solutions, analyzing structured and unstructured data, forming descriptive analysis and dashboards, and developing models for inference and prediction. 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:
- Engineering tables and jobs using Spark SQL and Python to meet analysis and reporting needs
- Creating interactive and drill-down dashboards to deliver key trends and insights to stakeholders
- Working with leaders and domain experts to identify business needs, create an analysis plan, identify deliverables, and communicate key insights
- Designing and implementing the data science model appropriate to the business challenge (classification, regression, unsupervised learning, recommendation systems, sentiment analysis, neural network, etc.)
- Communicating complex technical concepts to stakeholders with confidence and integrity
- Working with business stakeholders to determine metrics for evaluating the models
- Working with data engineers to create datasets for insight and prediction
- Building data visualizations, reports, and presentations
- Rapidly learning and implementing new technologies and tools
- Provide leadership to help shape our data initiatives across U-Haul
- Potential to share and teach skills around advanced data analytics and data evaluation
- Handling a variety of responsibilities under pressure and functioning independently
Relevant tasks:
- Formulate mathematical or simulation models of problems, relating constants and variables, restrictions, alternatives, conflicting objectives, and their numerical parameters.
- Perform validation and testing of models to ensure adequacy, and reformulate models, as necessary.
- Collaborate with senior managers and decision makers to identify and solve a variety of problems and to clarify management objectives.
- Present the results of mathematical modeling and data analysis to management or other end users.
- Collaborate with others in the organization to ensure successful implementation of chosen problem solutions.
- Analyze information obtained from management to conceptualize and define operational problems.
- Study and analyze information about alternative courses of action to determine which plan will offer the best outcomes.
- Prepare management reports defining and evaluating problems and recommending solutions.
- Define data requirements, gather and validate information, apply judgment and statistical tests.
- Observe the current system in operation and gather and analyze information about each of the component problems, using a variety of sources.
- Breakdown systems into their components, assign numerical values to each component, and examine the mathematical relationships between them.
- Design, conduct, and evaluate experimental operational models in cases where models cannot be developed from existing data.
- Educate staff in the use of mathematical models.
- Specify manipulative or computational methods to be applied to models.
- Develop and apply time and cost networks to plan, control, and review large projects.
- Develop business methods and procedures, including accounting systems, file systems, logistics systems, and production schedules.
Qualifications:
- Master's degree from an accredited college/university in Business Analytics, Computer Science, Statistics, Mathematics, Engineering, or related fields, with 3 years of relevant experience
- Proven experience in SQL and Python
- Proven experience in Power BI and Databricks
- Proven experience processing and analyzing structured and unstructured data
- Exposure to and familiarity with common statistical and machine learning techniques.
- Substantial depth in one or more of the above techniques with past industry projects and/or academic research.
- The ability to communicate and present both orally and in writing, and comfortability with ambiguity and change
- High degree of drive, energy, self-confidence, commitment, and flexibility
UHaul Offers:
- Medical insurance
- Prescription drug plans
- Dental & Vision plan with hearing care discounts
- Onsite medical clinic for team members and eligible family members
- New indoor fitness gym (Midtown Phoenix campus)
- Get Fit Gym Reimbursement Program
- Registered Dietitian Program
- WeightWatchers
- CVS Virtual Care
- UHaul Kids Program
- 24Hour Nurse Line
- Wellness Program (Healthier You initiatives & challenges)
- Mindset App Reimbursement
- Pet Insurance & Wellness plans
- Career stability
- Opportunities for advancement
- Valuable onthejob training
- Tuition Reimbursement Program
- Free online courses for personal and professional development at UHaul University
- 401(k) Savings Plan
- Employee Stock Ownership Plan (ESOP)
- Companypaid life insurance
- Voluntary life insurance options
- Short-Term and LongTerm Disability
- Critical Illness, Accident & Hospital Indemnity plans
- Business & business travel insurance
- MetLaw Legal Program
- MetLife Auto & Home Insurance
- LifeLock Identity Theft Protection
- Dave Ramsey's SmartDollar Financial Wellness Program
- UHaul Federal Credit Union
- Paid holidays, vacation, and sick time
- You Matter Employee Assistance Program (EAP)
- Discounts on cell phone plans, hotels, computers, vehicles & more
- Community involvement & volunteer opportunities
- UHaul Mothers Program (Paid maternity leave)
#LI-FT1
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.