Data Scientist Resume Examples
Years of Experience
- Entry-level
- Mid-career
- Senior-level
Jamila Amari
(456) 789-0123
[email protected]
144 Second Avenue, Raleigh, NC 23456
Profile
A Data Scientist with three years of professional experience, specializing in Python, machine learning, Big Data, and data management. Adept at performing statistical analysis on large, complex data sets to drive business intelligence and enhance data visualization.
Professional Experience
Junior Data Scientist, Omega Real Estate, Raleigh, NC
July 2017 – Present
- Collaborate with team members to improve customer relationship management database, leading to improved customer service outcomes in a high-volume real estate firm
- Used predictive analytics including data mining techniques to forecast company sales with 94% accuracy
- Increase data security by updating encryption, IP security and wireless transmission processes
Data Scientist Intern, Delta Security, Raleigh, NC
June 2016 – September 2016
- Gathered and analyzed information relating to system security and cyber threat intelligence
- Utilized analytics involving large datasets to improve models for cyber threat indicators
- Helped develop new algorithms to improve system accuracy and security
Key Skills
- Statistical Analysis
- Machine Learning
- Languages: C++, R, Python
- Data Management
- Big Data
Education
Master of Science in Analytics
North Carolina State University – Raleigh, Raleigh, NC, September 2015 – June 2017
Bachelor of Science in Mathematics
University of Wisconsin – Madison, Madison, WI, September 2011 – June 2015
Joshua Robertson
(789) 123-4560
[email protected]
2434 Third Road, San Antonio, TX 34567
Profile
An SAS certified Data Scientist with eight years of experience using predictive analytics and classical modeling techniques to provide valuable data insights for the financial industry. A proven track record of managing data analytics to support financial management, operations, and reporting for enterprise clients.
Professional Experience
Data Scientist, Financial Data Consulting Inc., San Antonio, TX
April 2016 – Present
- Deliver data science consulting services to enterprise clients within the financial sector valued at $20M-$35M, develop algorithms and analytical models using SAS, R, and Hadoop, and educate technical and non-technical audiences on findings and data trends
- Collaborate cross-functionally with data analytics, finance, and business intelligence departments to analyze complex financial data sets and improve forecasting methodologies for client businesses
- Utilize machine learning techniques to enhance financial reporting and data visualization
Data Scientist, Gamma Finance, Dallas, TX
July 2012 – March 2016
- Analyzed datasets and communicated insights to business owners to assist with data-driven decision making
- Developed dashboards and reports that communicate a story and provide visualization of data in a way that can be best utilized by internal customers
- Evaluated business processes and recommend data science solutions to improve efficiency
Education
Master in Data Science and Analytics
University of Oklahoma, Norman, OK, September 2011 – June 2012
Bachelor of Science of Information Technology
University of Tulsa, Tulsa, OK, September 2007 – June 2011
Key Skills
- Data Visualization
- Machine Learning
- SQL
- Hadoop
- Risk Analysis
- Software Engineering
Certifications
- Senior Data Scientist, Data Science Council of America, 2018
- SAS Certification, 2019
Elena Hernandez
(321) 987-6543
[email protected]
552 Fourth Boulevard, Buffalo, NY 45678
Profile
A Senior Data Scientist with 10+ years of experience using machine learning, Big Data, and deep learning to deliver data-driven solutions for enterprise organizations. A proven track record of creating dynamic machine learning algorithms to enhance data visualization and drive positive business outcomes.
Professional Experience
Senior Data Scientist, Omicron Biotech, Buffalo, NY
January 2012 – Present
- Collect, study, and interpret large datasets of research results to enhance data-driven decision making for a $100M biotechnology company and develop advanced machine learning models
- Oversee a 20-person business intelligence team, manage data analytics on an enterprise scale, and ensure appropriate implementation of statistical analysis, predictive modeling, and deep learning approaches
- Communicate data using a variety of visualization approaches, including Power BI and Tableau
Data Scientist, Kappa Corporation, Albany, NY
July 2009 – December 2011
- Led big data machine learning initiative to develop and deploy algorithms, which enhanced data visualization and supported a 200% increase in business growth over three years
- Developed model to accurately predict fraud activity, resulting in a 75% decrease in company losses
- Utilized R, Python and SAS to link data collected on-platform and off-platform to create thorough datasets that predict successful product development initiatives
Education
Master of Science in Data Science
New York University, New York, NY, September 2007 – June 2009
Bachelor of Arts in Computer Science
University of California – Berkeley, Berkeley, CA, September 2003 – June 2007
Key Skills
- Experience leading multi-disciplinary teams
- Coding skills in R, Python, C++, Java
- Big data, data mining and data visualization
- Risk analysis and problem solving skills
- MySQL and JSON
Certifications
- Microsoft Certified Solutions Expert, 2019
- SAS Certified Big Data Professional, 2017
Common Key Skills and Action Verbs for Data Scientist Resumes
Highlighting key skills and appropriate action verbs can be crucial to getting your resume noticed. Hiring managers use applicant tracking systems (ATS) to scan resumes and evaluate them based on the number of keywords and phrases that are included. Those with a higher match are highlighted for hiring managers, so the more keywords you include on your resume, the greater the chances of being invited for an interview.
| Key Skills & Proficiencies | |
|---|---|
| Big Data | Business Intelligence |
| C++ | Communication |
| Data Analytics | Data Architecture |
| Data Management | Data Science |
| Data Visualization | Data-driven Decision Making |
| Deep Learning | Hadoop |
| Java | Machine Learning |
| Predictive Modeling | Power BI |
| Process improvement | Python |
| R | Risk Analysis |
| Statistics | Tableau |
| Action Verbs | |
|---|---|
| Analyzed | Built |
| Conducted | Coordinated |
| Collaborated | Created |
| Designed | Developed |
| Diagnosed | Drove |
| Enhanced | Evaluated |
| Executed | Generated |
| Identified | Implemented |
| Improved | Integrated |
| Led | Managed |
| Oversaw | Partnered |
| Performed | Supported |
Tips for Writing a Better Data Scientist Resume
Highlight Your Leadership and Communication Skills
Data science requires much more than crunching numbers. While you should definitely emphasize your data science hard skills and experiences, it’s also important to show hiring managers your leadership and communication skills. After you analyze data you must be able to clearly communicate your insights to team members, business units, and clients, including those who may not have a strong knowledge of data science. In addition to communication, employers look for those who can lead and work in a team. In the example below, the candidate is able to emphasize their cross-functional leadership experience and communication skills using specific career achievements:
- Deliver data science consulting services to enterprise clients within the financial sector valued at $20M-$35M, develop algorithms and analytical models using SAS, R, and Hadoop, and educate technical and non-technical audiences on findings and data trends
- Collaborate cross-functionally with data analytics, finance, and business intelligence departments to analyze complex financial data sets and improve forecasting methodologies for client businesses
Showcase Your Data Science Expertise Using Career Achievements
Although you should make a point to list your technical skills in your professional profile and skills sections on your resume, the best way to demonstrate your expertise as a data scientist is by highlighting your career achievements. It’s one thing to say that you have knowledge of machine learning, it’s another thing entirely to say that you created machine learning models to support forecasting for a multi-million dollar organization. Try to incorporate hard numbers and data where applicable, as this also helps to provide valuable context for the hiring manager:
- Collect, study, and interpret large datasets of research results to enhance data-driven decision making for a $100M biotechnology company and develop advanced machine learning models
- Oversee a 20-person business intelligence team, manage data analytics on an enterprise scale, and ensure appropriate implementation of statistical analysis, predictive modeling, and deep learning approaches
- Communicate data using a variety of visualization approaches and tools,including Power BI and Tableau
How to Align Your Resume With the Job Description
According to the Bureau of Labor Statistics, jobs for data scientists, also known as computer and information research scientists, are projected to grow by 21% from 2021 to 2031. This increase in growth is mainly driven by businesses that are increasingly collecting data to gain insights on customer preferences and behavior.
Although the number of jobs for data scientists is expected to grow, it’s likely that there will continue to be strong competition on the open market. A well-written resume can help you stand out from other job applicants and increase your chances of being interviewed. Hiring managers use job descriptions to define the skills and experience an applicant would need to be successful in their company and the position they’re trying to fill. In order to stand out from other candidates, it’s important to include the keywords that match what the hiring manager has detailed.
If you’re not sure what to feature, start by highlighting the requirements listed in the job description. Generally requirements that are listed first or mentioned more than once are the most important. Ensure your resume describes how you can deliver on these key priorities. You can stop your resume from sounding generic by focusing on notable contributions and avoiding copy and pasting. Prospective employers want to see tangible examples of you using your data science expertise from your career, so you’ll want to highlight relevant achievements that are aligned with the job you’re applying for. This strategy maximizes the impact of your resume and greatly increases your chances of securing your next big opportunity.