How to hire a senior data scientist

How to hire a senior data scientist, step by step

Here's a step-by-step senior data scientist hiring guide:

• Step 1: Identify your hiring needs
• Step 2: Create an ideal candidate profile
• Step 3: Make a budget
• Step 4: Write a senior data scientist job description
• Step 5: Post your job
• Step 6: Interview candidates
• Step 7: Send a job offer and onboard your new senior data scientist
• Step 8: Go through the hiring process checklist

What does a senior data scientist do?

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1. Identify your hiring needs

   Before you start hiring a senior data scientist, identify what type of worker you actually need. Certain positions might call for a full-time employee, while others can be done by a part-time worker or contractor.

   Determine employee vs contractor status

   Is the person you're thinking of hiring a US citizen or green card holder?

   Yes

   No

   A senior data scientist's background is also an important factor in determining whether they'll be a good fit for the position. For example, senior data scientists from different industries or fields will have radically different experiences and will bring different viewpoints to the role. You also need to consider the candidate's previous level of experience to make sure they'll be comfortable with the job's level of seniority.

   This list shows salaries for various types of senior data scientists.

   Type of Senior Data Scientist	Description	Hourly rate
   Senior Data Scientist	Computer and information research scientists invent and design new approaches to computing technology and find innovative uses for existing technology. They study and solve complex problems in computing for business, medicine, science, and other fields.	$43-81
   Research And Development Internship	When it comes to Research and Development Internship, the duties will vary according to the organization or company. Most of the time, the responsibilities will revolve around observing the industry, taking part in the research and analysis, lend a helping hand in experiments and surveys, explore theories and attempt to create a model of out it, present findings for evaluation, and develop more innovative designs and systems... Show more	$14-22
   Data Engineer	A data engineer is someone who makes data science possible. This IT job requires the search for data set trends and algorithm development to make raw data more beneficial to the enterprise... Show more	$38-71

   Show more

2. Create an ideal candidate profile

   Common skills:

   • Python
   • Data Science
   • Visualization
   • Java
   • Data Analysis
   • Hadoop
   • Predictive Models
   • TensorFlow
   • Machine Learning Techniques
   • Scala
   • Statistical Analysis
   • Machine Learning Algorithms
   • AWS
   • Healthcare

   Check all skills

   Responsibilities:

   • Administrate SharePoint database access; manage classified documents and applications.
   • Configure and manage JobScope ERP system for a make-to-order/make-to-stock design and manufacturing environment.
   • Administer business intelligence systems and done business data analysis, visualization and reporting.
   • Develop MapReduce jobs in java for data cleaning and preprocessing.
   • Integrate internal and external data via API for cross platform marketing campaign evaluations.
   • Diagnose denial of service attacks and improve security using AWS security groups and network ACLs.

   More senior data scientist duties

3. Make a budget

   Including a salary range in your senior data scientist job description is one of the best ways to attract top talent. A senior data scientist can vary based on:

   • Location. For example, senior data scientists' average salary in hawaii is 48% less than in washington.
   • Seniority. Entry-level senior data scientists 47% less than senior-level senior data scientists.
   • Certifications. A senior data scientist with certifications usually earns a higher salary.
   • Company. Working for an established firm or a new start-up company can make a big difference in a senior data scientist's salary.

   Average senior data scientist salary

   $124,093yearly

   $59.66 hourly rate

   ---

   Entry-level senior data scientist salary

   $90,000 yearly salary

   Updated December 17, 2025

   Average senior data scientist salary by state

   Rank	State	Avg. salary	Hourly rate
   1	California	$146,708	$71
   2	Washington	$140,678	$68
   3	New York	$111,586	$54
   4	Massachusetts	$109,692	$53
   5	New Jersey	$106,830	$51
   6	Connecticut	$105,462	$51
   7	Arizona	$103,322	$50
   8	Pennsylvania	$102,216	$49
   9	Utah	$102,045	$49
   10	District of Columbia	$101,253	$49
   11	Virginia	$98,582	$47
   12	Texas	$98,260	$47
   13	Nebraska	$94,230	$45
   14	Michigan	$93,939	$45
   15	North Carolina	$93,848	$45
   16	Colorado	$92,601	$45
   17	Illinois	$91,446	$44
   18	Ohio	$89,332	$43
   19	Minnesota	$88,665	$43
   20	Georgia	$88,245	$42

   Average senior data scientist salary by company

   Company

   Rank	Company	Average salary	Hourly rate	Job openings
   1	Brex	$187,843	$90.31	3
   2	Credit Karma	$184,214	$88.56	7
   3	Airbnb	$182,554	$87.77
   4	Netflix	$180,052	$86.56	9
   5	Coinbase	$180,001	$86.54	289
   6	Roku	$173,478	$83.40	3
   7	Wealthfront	$173,163	$83.25
   8	SmartAsset	$172,270	$82.82
   9	ByteDance	$170,143	$81.80	7
   10	Meta	$168,751	$81.13	1,250
   11	Flexport	$165,020	$79.34
   12	Earnest Research	$164,224	$78.95
   13	Discovery	$162,278	$78.02
   14	DoorDash	$161,353	$77.57	23
   15	Chegg	$161,294	$77.55
   16	Bill.com	$161,243	$77.52	16
   17	Twitter	$161,232	$77.52
   18	TikTok	$160,914	$77.36	144
   19	Turner Broadcasting	$160,785	$77.30
   20	The Walt Disney Company	$159,794	$76.82	78

4. Writing a senior data scientist job description

   A senior data scientist job description should include a summary of the role, required skills, and a list of responsibilities. It's also good to include a salary range and the first name of the hiring manager. To help get you started, here's an example of a senior data scientist job description:

   Senior data scientist job description example

   Want to push the envelope on human-computer interaction at Apple? Contribute to a product that is redefining mobile and desktop computing, and work with the people who are building the intelligent assistant that helps millions of people get things done - just by asking! Our vision for the Siri Data organization is to improve Siri by using data as the voice of our customers. Within this organization the mission of the Analytics team is to inform the evolution of Siri through measurement and analysis of the user experience. Part of this mission is achieved through evaluation and experimentation; as a Data Scientist, you will help to evolve our core methods and technologies. Opportunities open in Cupertino, CA and Seattle, WA.
   Key Qualifications
   
   Expertise in statistical modeling, study design, human computation, and knowledge of how to leverage these skills to solve complex business problems Excellent written and verbal communication skills with the ability to explain technical topics to data scientists, engineers, and business partners Data-querying skills (SQL and/or Spark, etc.) Experience with a scripting language for statistical modeling and data processing (e.g., Python, R, or Scala) Ability to stay focused and prioritize competing demands while achieving exceptional quality History of building and managing cross-functional partnerships Innovative, collaborative, and product focused
   
   Description
   
   The AI/ML Data Organization is seeking a talented Data Scientist to conduct human evaluation methodology research! Your work will provide the building blocks for evaluating and improving our Siri product. You will drive core metrics and help to produce annotated data sets that empower engineering teams to improve Siri.You will: - Conduct R&D to drive metrics development and evaluation methods - your work will drive sound statistical inferences about Siri product quality - Deep dive into complex business problems and determine how we can best engineer our evaluation systems to produce information that influence business decisions - Partner closely with cross functional teams (engineers, PMs, analysts) to get your methodological developments translated into technologies that Siri engineering will use to evaluate and improve Siri
   
   Education & Experience
   
   Cognitive Science, Statistics, Economics, Sociology, or other quantitative fields.Prefer advanced degree + 3 years of industry experience.

   Copy this example

   

5. Post your job

   To find the right senior data scientist for your business, consider trying out a few different recruiting strategies:

   • Consider internal talent. One of the most important sources of talent for any company is its existing workforce.
   • Ask for referrals. Reach out to friends, family members, and current employees and ask if they know or have worked with senior data scientists they would recommend.
   • Recruit at local colleges. Attend job fairs at local colleges to recruit senior data scientists who meet your education requirements.
   • Social media platforms. LinkedIn, Facebook and Twitter now have more than 3.5 billion users, and you can use social media to reach potential job candidates.

   Post your job online:

   • Post your senior data scientist job on Zippia to find and attract quality senior data scientist candidates.
   • Use niche websites such as dice, engineering.com, stack overflow, it job pro.
   • Post a job on free websites.

6. Interview candidates

   During your first interview to recruit senior data scientists, engage with candidates to learn about their interest in the role and experience in the field. During the following interview, you'll be able to go into more detail about the company, the position, and the responsibilities.

   It's also good to ask about candidates' unique skills and talents. You can move on to the technical interview if a candidate is good enough for the next step.

   If your interviews with senior data scientist applicants aren't enough to make a decision, you should also consider including a test project. These are often the best, most straightforward, and least bias-prone ways of determining who will likely succeed in the role. If you don't know how to design an appropriate test, you can ask someone else on the team to create it or take a look at these websites to get a few ideas:

   • TestDome
   • CodeSignal
   • Testlify
   • BarRaiser
   • Coderbyte

   The right interview questions can help you assess a candidate's hard skills, behavioral intelligence, and soft skills.

7. Send a job offer and onboard your new senior data scientist

   Once you've selected the best senior data scientist candidate for the job, it's time to write an offer letter. In addition to salary, this letter should include details about the benefits and perks you offer the candidate. Ensuring that your offer is competitive is essential, as qualified candidates may be considering other job opportunities. The candidate may wish to negotiate the terms of the offer, and you should be open to discussion. After you reach an agreement, the final step is formalizing the agreement with a contract.

   You should also follow up with applicants who don't get the job with an email letting them know that you've filled the position.

   Once that's done, you can draft an onboarding schedule for the new senior data scientist. Human Resources should complete Employee Action Forms and ensure that onboarding paperwork is completed, including I-9s, benefits enrollment, federal and state tax forms, etc. They should also ensure that new employee files are created for internal recordkeeping.

8. Go through the hiring process checklist

   • Determine employee type (full-time, part-time, contractor, etc.)
   • Submit a job requisition form to the HR department
   • Define job responsibilities and requirements
   • Establish budget and timeline
   • Determine hiring decision makers for the role
   • Write job description
   • Post job on job boards, company website, etc.
   • Promote the job internally
   • Process applications through applicant tracking system
   • Review resumes and cover letters
   • Shortlist candidates for screening
   • Hold phone/virtual interview screening with first round of candidates
   • Conduct in-person interviews with top candidates from first round
   • Score candidates based on weighted criteria (e.g., experience, education, background, cultural fit, skill set, etc.)
   • Conduct background checks on top candidates
   • Check references of top candidates
   • Consult with HR and hiring decision makers on job offer specifics
   • Extend offer to top candidate(s)
   • Receive formal job offer acceptance and signed employment contract
   • Inform other candidates that the position has been filled
   • Set and communicate onboarding schedule to new hire(s)
   • Complete new hire paperwork (i9, benefits enrollment, tax forms, etc.)

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