Data Scientist Jobs in the United States

Data Science Jobs Overview

With the development of Web 2.0 applications in the early 2000s, suddenly huge datasets started to be collected. Fast forward a decade and Big Data was born. In no time it became clear what a massive opportunity lay ahead. Data science jobs are your opportunity to make sense of it. You’ll study and translate data into valuable information to help companies and government organizations make important decisions.

Data scientists are extremely sought-after as they are crucial in almost every industry. Think about the way you can easily unlock your phone with your face, how you get personalized shopping recommendations, or the way your favorite streaming service suggests exactly the right shows for you. That’s data science. Data scientist jobs typically include tasks such as:

• Gathering and extracting relevant data from various sources such as databases or web scraping.
• Identify trends and potential insights that can guide business decision-making.
• Choose suitable machine learning algorithms or statistical models based on the nature of the problem to solve.
• Assess model performance using appropriate metrics.
• Prepare reports, visualizations, and presentations to highlight key takeaways from data analysis.

Data science jobs are generally full-time office or remote positions on nine-to-five schedules.

Salaries for Data Science Jobs

The salary for data scientists sits between $79,183 and $133,041 per year with $108,546 as the median. Depending on your industry, location, and specialization you can also achieve higher figures.

Check out the top-paying industries for data science jobs and their average annual wage:

• clothing and clothing accessories retailers: $164,030
• computer and peripheral equipment manufacturing: $158,350
• semiconductor and other electronic component manufacturing: $148,270
• automotive parts, accessories, and tire retailers: $143,290
• securities, commodity contracts, and other financial investments and related activities: $133,730

Data scientist jobs also pay the highest in the following states:

• California: $147,390 per year
• Washington: $140,780 per year
• Virginia: $133,990 per year
• Delaware: $133,320 per year
• New Jersey: $129,980 per year

Explore Monster’s Salary Tool to learn what skills could take you there. Whichever career stage you’re in, on Monster there are plenty of resources to help you max out your salary.

How to Find the Best Data Science Jobs

Finding the right data scientist job requires a combination of self-assessment and research. Below is our suggested course of action.

Define Your Interests and Strengths

Start by identifying your interests and framing your technical skills. It could be programming languages, machine learning algorithms, data visualization, statistical analysis or more. Next, recognize your soft skills like problem-solving, communication or teamwork.

Screen Companies

Consider which industries align with your interests. As a data scientist, you have opportunities in technology, finance, healthcare and many more. After you narrow it down to an industry, look for companies whose values and culture resonate with you.

Analyze Job Listings

When browsing through data science jobs, pay attention to the specific tasks, qualifications and technology listed. Ensure they are in line with your experience and skills, and what drives you. Next, analyze the tone and language of the job ad. Is it casual or formal? What kind of skills does it emphasize? All of that can tell you a lot about the company’s work environment.

How to Apply to Data Science Jobs

Data scientist jobs are abundant but that doesn’t mean they can’t be competitive. Craft a compelling resume and cover letter to stand out from the competition with the following tips.

Update Your Resume for Data Scientist Jobs

Before jumping into the job market, write a strong resume that urges hiring managers to give you that all-important call. Focus on your core competencies and carefully choose keywords from the job listing like:

• Data analysis
• Data mining
• Machine learning
• Python
• AWS

Look at our data scientist resume sample for further guidance. If you have limited experience, make sure to emphasize your transferrable skills. Employers prefer candidates who showcase the ability to continuously grow and learn, rather than having a fixed set of expertise.

Other qualities that are highly valued in data scientist candidates include soft skills, such as:

• communication
• curiosity
• adaptability
• teamwork
• problem solving
• critical thinking

After adding your skills, highlight how effective your work is. To do so, focusing on KPIs is your best bet. Some of the most used in the data science field are:

• model accuracy
• data quality metrics
• data processing time
• data retention rates

For more help, reach out to Monster’s Resume Writing Services. We help you showcase your experience and skills to gain more attention and secure more interviews.

Data Scientist Job Cover Letter

Since your resume must stay within a two-page limit, write a cover letter to allow you to expand. It helps you turn the recruiter’s attention exactly where you want it, making sure that no important detail gets passed by.

• Start with a strong opening that highlights your passion for leveraging data to drive insights.
• Mention projects or experiences that support your claims of proficiency in data science, machine learning, or statistical analysis.
• Reference your skills as a solution to the company’s needs. The more specific you can be the better.
• Show enthusiasm and eagerness to contribute to the company’s data-driven success.

Can’t wait to make sense of data to better understand people’s habits and improve businesses? Upload your resume and cover letter on Monster candidate account. You can also activate job alerts so you never miss a chance to be selected.

How to Follow Up with an Employer

You applied for data science jobs but haven’t heard back. Wondering if there is anything you can do? Send a short follow-up email to the employers to increase your chances of selection. It won’t take long. Here is how to do it in a few easy steps:

• Wait strategically. Leave a week or so before reaching out. The hiring team needs time to screen candidates and set up interviews.
• Personalize the greeting. Avoid the generic “To Whom It May Concern”. Instead, look up the hiring manager’s name in the job ad or by calling the company.
• Mention your application. Briefly mention what role you applied for and when.
• Highlight alignment. Give a short overview of your experience in the field, and which skills of yours best match the job requirements.
• Express interest. Politely ask for an update about your application and renew your interest in the position.
• Close professionally. Invite the recruiter to review your attached resume and thank them for their time.

Interviewing Tips for Data Science Jobs

Once your resume gets selected, that’s when the fun begins. It’s time to prepare for the job interview. Start by strengthening your foundations and refresh your answers to common interview questions, such as:

• What are your weaknesses?
• Why should we hire you?
• Why do you want to work here?
• Why do you want to leave your current job?

Next, carefully revise technical topics they might ask you about, like:

• programming languages
• data manipulation and analysis techniques
• statistics models

Then, think about how to talk about your experiences and skills, trying to add measurable accomplishments like you did in your resume. Many recruiters use hypothetical situations to test how you’d react through behavioral questions. Approach them with the STAR method.

Have a look at other common interview questions for data analysts, and learn to tackle them. Finally, be aware of your body language. Non-verbal language is a very powerful tool to master.

What to Do When You Get an Offer

Did you receive the job offer for the data scientist role you were hoping for? Celebrate as you should, then, follow these steps before making a decision:

• Express appreciation. Take time to thank the hiring manager and acknowledge the recruitment efforts, regardless of if you’re going to accept or decline the offer.
• Give yourself time. Don’t feel pressured to provide an immediate response. It’s perfectly acceptable to take between 48 hours and a week to decide. Just make sure to communicate clearly with the employer.
• Evaluate the offer. Examine the compensation package, including salary, and bonuses, and Consider benefits such as health insurance, retirement plans and other perks.
• Assess company fit. After getting to know the company better during the interviews, re-evaluate one last time if you’d fit in with its culture and values. Consider also what kind of career development prospects you’d have with them.
• Ask questions and negotiate. If you have any uncertainties about the offer or believe that your profile deserves more, don’t be afraid to ask questions or start a negotiation.

Data Science Job Career Paths

After gaining experience in data science jobs for a few years, you could take your career to the next level in the following roles:

• Data science manager: A natural progression in the data science field is to become a manager. You’d lead a team of data scientists and analysts, manage projects, and set the team’s strategy.
• Machine learning engineer: If you choose to pursue a career as a machine learning (ML) engineer you’ll focus on designing and deploying complex ML models and systems. You’ll also collaborate with other data scientists and software engineers.
• Data science architect: In this role you’ll design and implement the data science infrastructure and ecosystem within an organization. They create the framework for data collection, processing, and storage as well as design systems that support model training.
• Chief data officer (CDO): As a CDO, you’d be responsible for the overall data strategy of your company. You’d align data initiatives with business objectives, ensure privacy compliance and lead data-driven decision-making.

Similar Occupations

Are you unsure which computer jobs would be best for you? Why not also have a look at:

• data architect jobs
• machine learning jobs
• applications analyst jobs
• AI jobs