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] LinkedIn | Portfolio
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] LinkedIn | Portfolio
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
John Bergsen
(123) 456-7890 [email protected] LinkedIn | Portfolio
Philadelphia, PA 12345
LinkedIn | Portfolio
Profile
A dynamic data scientist with six years of experience specializing in deep learning, AI, and ML. A strong history of developing cutting-edge deep learning modules to enhance data visualization and facilitate strategic decision-making.
Professional Experience
Senior Data Scientist, Liberty Data Science Solutions, Philadelphia, PA
October 2021 – present
Manage and build a diverse team of developers, solution architects, and data scientists to develop state-of-the-art ML, AI, and deep learning solutions for enterprise clients valued at up to $32 million
Develop project strategy, evaluate client business needs and requirements, and communicate concepts to non-technical stakeholders to drive AI adoption
Perform comprehensive analysis of large data sets to ensure proper implementation of ML/AI solutions and drive positive business outcomes
Data Scientist, Starlight Technologies, Philadelphia, PA
June 2018 – October 2021
Managed and preprocessed large datasets, including cleaning, normalizing, and transforming data, resulting in a 17% improvement in model accuracy
Collaborated with cross-functional teams, including software engineers and product managers, to develop and integrate deep learning models into the product suite, contributing to a 24% increase in user engagement
Key Skills
Deep learning
ML
AI
Data visualization
Technical project management
Certifications
Certified Data Scientist (DASCA-CDS), Data Science Council of America, 2018
Education
Bachelor of Science (B.S.) Data Science
Temple University, Philadelphia, PA | June 2018
Meera Patel
(123) 456-7890 [email protected] LinkedIn | Portfolio
San Francisco, CA 12345
LinkedIn | Portfolio
Profile
A lead data scientist with seven years of experience specializing in predictive models, ML, team management, and cross-functional leadership. A proven track record of leading data science teams to develop sophisticated data science solutions and enhance business decision-making.
Professional Experience
Lead Data Scientist, Rush Data Science Inc., San Francisco, CA
October 2020 – present
Lead a team of junior analysts to interpret complex data sets and develop predictive models using Python to enhance data-driven decision-making, contributing to a 34% increase in revenue over two years
Create comprehensive data visualization reports using Tableau to support non-technical team members and stakeholders in understanding complex data patterns
Build and analyze ML models and oversaw algorithm training to enhance effectiveness and accuracy of data analytics
Data Scientist, West Star Technologies, San Francisco, CA
June 2017 – October 2020
Analyzed and interpreted complex data sets using statistical tools, contributing to significant improvements in business decision-making and a 15% increase in revenue
Developed ML algorithms using R, which improved the accuracy of predictive analytics by 25%
Managed SQL databases, ensuring data integrity and accessibility for the entire data science team
Key Skills
Data analytics
ML
Python
AI
Data integrity
Certifications
Certified Data Scientist (DASCA-CDS), Data Science Council of America, 2017
Education
Bachelor of Science (B.S.) Data Science
University of San Francisco, San Francisco, CA | June 2017
A results-driven data scientist with six years of experience developing and implementing ML models, analyzing complex datasets, and collaborating with cross-functional teams to deliver scalable data science solutions for enterprise organizations.
Professional Experience
Machine Learning Data Scientist, Coulthart Financial, Miami, FL | July 2021
present
Develop and integrate scalable ML algorithms to enhance the product suite of an enterprise financial firm with over $200 million in assets under management (AUM)
Manage and build a team of 15 data scientists, engineers, and developers, oversee all aspects of data analytics, and ensure proper implementation of ML techniques and predictive modeling
Perform comprehensive data analysis to identify patterns and trends and leverage insights to enhance the effectiveness of data analytics
Machine Learning Data Scientist, Rosenberg Finance, Miami, FL
June 2018 – October 2021
Utilized Python and ML libraries to develop predictive models for the firm’s cloud services, contributing to a 16% increase in customer retention
Conducted exploratory data analysis to inform the development of cloud services and new product features
Coordinated cross-functionally with business analysts to analyze and translate business needs into technical requirements
Key Skills
ML
Deep learning
Statistical analysis
Cross-functional collaboration
Data analysis
Certifications
Certified Data Scientist (DASCA-CDS), Data Science Council of America, 2018
Education
Bachelor of Science (B.S.) Data Science
University of Florida, Gainesville, FL | June 2018
Aliya Jackson
(123) 456-7890 [email protected] LinkedIn | Portfolio
New York, NY 12345
LinkedIn | Portfolio
Profile
An innovative data scientist with eight years of experience specializing in natural language processing, ML, and deep learning. A strong history of developing and integrating impactful data science solutions to enhance the delivery of patient care in clinical environments.
Professional Experience
NLP Data Scientist, St. Augustine’s Hospital, New York, NY
February 2019 – present
Lead the development and implementation of ML, AI, and deep learning models to support the delivery of patient care for a 500-bed hospital, contributing to an 8% reduction in mortality rates
Train and develop ML algorithms to aid the development of treatment plans based on symptoms, patient medical history, and medical risks
Manage a team of seven data scientists and analysts, provide training, and deliver coaching to facilitate professional development
NLP Data Scientist, Brooklyn Children’s Hospital, New York, NY
June 2016 – February 2019
Developed and trained ML models for natural language processing tasks to provide valuable insights for clinical teams, resulting in a 17% reduction in response times and a 12% increase in patient satisfaction
Collaborate cross-functionally with physicians and medical staff to enhance the effectiveness of predictive modeling
Key Skills
Natural language processing (NLP)
ML
AI
Data analytics
Predictive modeling
Certifications
Certified Data Scientist (DASCA-CDS), Data Science Council of America, 2016
Education
Bachelor of Science (B.S.) Data Science
University of Syracuse, New York, NY | June 2016
How To Write a Data Science Resume
In the realm of burgeoning artificial intelligence (AI) and machine learning (ML) advancements, your data science resume should showcase your proficiency in this rapidly expanding technological domain. As you navigate the diverse opportunities within this field, a compelling resume, driven by notable achievements, becomes your primary tool for standing out amidst fierce competition. We’ll provide valuable insights to help translate your data science experience into a powerful marketing document.
1. Write a dynamic profile summarizing your data science qualifications
Creating an engaging snapshot of your data science career is the best way to draw the reader in. Start by listing your job title, years of experience, and three to four specializations that align with the job posting. In the subsequent sentences, establish yourself as a thought leader within your space.
For example, if you helped to pioneer the integration of ChatGPT and other AI solutions, you’d feature this information directly in your profile. If you played a key role in developing ML and deep learning solutions for autonomous vehicles, display these achievements directly in your summary. Providing these insights will help tell your story and highlight the value you can bring to prospective employers.
Senior-Level Profile Example
A senior data scientist with over 10 years of experience using ML, big data, and deep learning to deliver data-driven solutions for enterprise organizations. A proven track record of creating dynamic ML algorithms to enhance data visualization and drive positive business outcomes.
Entry-Level Profile Example
A data scientist with three years of professional experience specializing in Python, ML, Big Data, and data management. Adept at performing statistical analysis on large, complex data sets to drive business intelligence and enhance data visualization.
2. Outline your data science experience in a compelling list
To craft an accomplishment-driven professional experience section, create bullet points emphasizing your career achievements rather than job responsibilities. Companies are interested in results, and as a data scientist, you must demonstrate the bottom-line value of your contributions by incorporating data, metrics, and monetary figures.
Emphasize your ability to collaborate with cross-functional teams and translate complex technical concepts into accessible language, as you won’t always work solely with data scientists on every project.
Senior-Level Professional Experience Example
Senior Data Scientist
Omicron Biotech, Buffalo, NY | October 2016 – present
Collect, study, and interpret large datasets of research results to enhance data-driven decision-making for a $100 million biotechnology company
Develop advanced ML 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
Entry-Level Professional Experience Example
Data Scientist
Omega Real Estate, Raleigh, NC | July 2021 – present
Collaborated 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
Increased data security by updating encryption, IP security, and wireless transmission processes
3. Outline your education and data science-related certifications
In addition to your education, feature any relevant certifications you’ve achieved throughout your data science career. Although most employers will be more interested in your professional experience, obtaining other credentials won’t hurt your chances of landing the interview.
For instance, having a Certified Analytics Professional (CAP) credential could be useful for entry-level professionals, as the exam will help test your knowledge across a wide range of data science concepts. A certification alone won’t guarantee an interview for senior-level job seekers, but it will show prospective employers you’re committed to continuous learning.
Education
Template
[Degree Name]
[School Name], [City, State Abbreviation] – [Graduation Month and Year]
Microsoft Certified Solutions Expert, Microsoft – 2019
SAS Certified Big Data Professional, SAS – 2017
4. List key data science skills and proficiencies
Most organizations rely on an applicant tracking system (ATS) to identify qualified candidates for job openings. To get your resume through the initial screening process and into the hiring manager’s hands, directly incorporate keywords from the job description into your profile, professional experience, and skills section. Below, you’ll find a list of key terms and skills that you may encounter while applying for data scientist positions:
Key Skills and Proficiencies
Agile methodology
AI
Big data
Business intelligence
Data analysis
Data analytics
Data-driven decision making
Data modeling
Data science
Data visualization
Deep learning
ML
Natural language processing (NLP)
Power BI
Predictive modeling
Python
R (programming language)
Statistics
SQL
Tableau
5. Highlight your leadership and communication skills
Data science requires much more than crunching numbers. While it’s best to 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 communicate your insights to team members, business units, and clients. This includes those who may not have a strong knowledge of data science. In addition to communication, employers look for people who can lead diverse teams and collaborate cross-functionally.
How To Pick the Best Data Scientist Resume Template
When selecting your template, prioritize structure and readability over visual appeal. Heavy colors and bulky graphics may look nice, but they can distract the reader from your content. Seek a template that organizes your content effectively and fits your brand. Hiring managers will always be more interested in your achievements and qualifications than the style of your template.
Frequently Asked Questions: Data Science Resume Examples and Advice
What are common action verbs for data science resumes?-
Action verbs help hiring managers visualize your contributions, but it’s easy to run short on action verbs during the resume-building process. Differentiating your word choice can enhance the quality of your bullet points and eliminate the appearance of redundancy.
Use these action verbs to craft your professional experience section:
Action Verbs
Analyzed
Built
Collaborated
Conducted
Created
Designed
Developed
Diagnosed
Drove
Enhanced
Evaluated
Executed
Identified
Implemented
Improved
Integrated
Led
Managed
Performed
Supported
How do you align your resume with a data scientist job description?-
According to the Bureau of Labor Statistics, jobs for data scientists (computer and information research scientists) are projected to grow by 21% from 2021 to 2031, faster than average for most occupations. This growth is primarily driven by the advancement of AI technologies and ML, which have become increasingly important for businesses.
Although these projections are highly optimistic, you must align your resume with the job description to secure interviews for the most lucrative opportunities. Data science is a highly competitive field, and tailoring your document to individual job postings will significantly increase your chances of landing your next job opportunity.
For example, suppose a company is looking for an expert in ML. In that case, you’d highlight further your knowledge of deep learning, supervised learning, and unsupervised learning to substantiate yourself as a thought leader in your space.
What is the best data science resume format?-
Reverse chronological format is ideal for data science resumes. This approach ensures your most recent and relevant experience is featured at the top of your document. It’s best to avoid functional resume formats even at the entry level. If you lack hands-on experience, you’d still be much better served by illustrating your academic projects than only listing technical skills.
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Providing a matching cover letter is a great way to help your application stand out in the open market. The cover letter allows you to tell prospective employers more about who you are as a professional and the value you can bring to their organization. In the middle paragraphs, mention something about the company’s reputation or mission statement and why this draws you to apply for the position. For more insights, view our data scientist cover letter guide.
Frank Hackett is a professional resume writer and career consultant with over eight years of experience. As the lead editor at a boutique career consulting firm, Frank developed an innovative approach to resume writing that empowers job seekers to tell their professional stories. His approach involves creating accomplishment-driven documents that balance keyword optimization with personal branding. Frank is a Certified Professional Resume Writer (CPRW) with the Professional Association of Resume Writers and Career Coaches (PAWRCC).
