Data Scientist Resume Skills and Keywords

What skills should I put on a data scientist resume?

The top skills to put on a data scientist resume are Python, R and Microsoft Office (Excel and PowerPoint), along with programming, mathematics, and computers and electronics. Employers also look for dependability, attention to detail and integrity, which are best shown through results in your bullet points rather than listed.

• Python
• R
• C++
• Microsoft Excel
• Microsoft PowerPoint
• Programming
• Mathematics
• Computers and Electronics knowledge
• Dependability
• Attention to Detail
• Integrity

What software should data scientists know?

Data scientist job postings most often ask for Python, R, C++, Microsoft Azure and Microsoft Office (Excel and PowerPoint). Many data scientists also use database management and business intelligence software; which products matter depends on the employer, so list the specific products a posting names and you have used.

• Python
• R
• C++
• Microsoft Azure
• Microsoft Power BI
• Tableau
• The MathWorks MATLAB
• Structured query language (SQL)
• SAS
• Amazon Web Services (AWS)
• Apache Spark
• Apache Hadoop
• Git
• Scikit-learn
• Snowflake
• TensorFlow
• PyTorch
• pandas
• NumPy
• Microsoft Excel
• Microsoft PowerPoint

What hard skills do employers want in data scientists?

Data scientists need programming, mathematics, and computers and electronics far more than most workers, and critical thinking more than most. Name these in your resume summary and prove each one with a bullet that shows you using it.

• Programming · Needed far more than in most jobs
  Writing computer programs for various purposes.
• Mathematics · Needed far more than in most jobs
  Using mathematics to solve problems.
• Computers and Electronics · Needed far more than in most jobs
  Knowledge of circuit boards, processors, chips, electronic equipment, and computer hardware and software, including applications and programming.
• Critical Thinking · Needed more than in most jobs
  Using logic and reasoning to identify the strengths and weaknesses of alternative solutions, conclusions, or approaches to problems.
• Complex Problem Solving · Needed more than in most jobs
  Identifying complex problems and reviewing related information to develop and evaluate options and implement solutions.
• Active Learning · Needed more than in most jobs
  Understanding the implications of new information for both current and future problem-solving and decision-making.

Compared with the average rating across all jobs in Department of Labor data.

What soft skills do data scientists need?

The most important soft skills for data scientists are dependability, attention to detail and integrity, followed by intellectual curiosity and achievement orientation. Show them through results in your bullet points rather than listing them as single words.

1. Dependability: A tendency to be reliable, responsible, and consistent in meeting work-related obligations.
2. Attention to Detail: A tendency to be detail-oriented, organized, and thorough in completing work.
3. Integrity: A tendency to be honest and ethical at work.
4. Intellectual Curiosity: A tendency to seek out and acquire new work-related knowledge and obtain a deep understanding of work-related subjects.
5. Achievement Orientation: A tendency to establish and maintain personally challenging work-related goals, set high work-related standards, and exert high effort toward meeting those goals and standards.

What keywords should a data scientist resume include?

A data scientist resume should include the exact tool names, skills and job title from the posting. For data scientists, common keywords include Python, R, Microsoft Office (Excel and PowerPoint), Analytics Consultant and Applied Scientist. Applicant tracking systems and recruiters scan for these words, so use them wherever they truthfully describe your experience.

How do I write data scientist resume bullet points?

Start each data scientist bullet point with a past-tense verb and a core task, such as “Recommended data-driven solutions to key stakeholders,” then end it with a measurable result: what changed, by how much, and for whom. These starters come from the job’s most important tasks.

What are other job titles for a data scientist?

Other job titles for a data scientist include Analytics Consultant, Applied Scientist, Data Analyst, Data Analytic Scientist and Data Analytics Scientist. Government job data groups them as “Data Scientists.” Search for these titles too, and use the posting’s exact title on your resume when it fits your experience.

• Analytics Consultant
• Applied Scientist
• Data Analyst
• Data Analytic Scientist
• Data Analytics Scientist
• Data Analytics Specialist
• Data Architect
• Data Consultant
• Data Economist
• Data Engineer
• Data Management Scientist
• Data Mining Analyst
• Data Modeler
• Data Quality Analyst
• Data Science Engineer
• Data Science Intern
• Data Specialist
• Machine Learning Data Scientist
• Machine Learning Engineer
• Machine Learning Scientist

What education do data scientists need?

Most data scientists need a bachelor's degree to get hired. No prior work experience is usually required. On your resume, list coursework or certifications in mathematics and computers and electronics.

How much do data scientists make?

Data scientists earn a median salary of $120,230 a year, according to May 2025 federal wage data. The lowest-paid 10% earn less than $67,240, and the highest-paid 10% earn more than $199,130. Employment is projected to grow 34.6% from 2025 to 2035, faster than the 3.5% average for all jobs, with about 24,800 openings a year.

What’s changing in this field

The Bureau of Labor Statistics expects these trends to shape hiring. If your experience touches any of them, say so.

• Demand change - share increases as larger amounts of digital and electronic data are collected over the projections decade. Businesses in all industries will hire data scientists to analyze data to help improve business processes and design and develop new products.

What other jobs can data scientists do?

Data scientists’ skills carry over best to jobs as statisticians, statistical assistants and financial quantitative analysts, which use the most similar skills and day-to-day work.