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A professional Data scientist with a clear goal: to use statistics and machine learning for finding complex data patterns that drive meaningful impact on the business. In previous roles I built a model for predicting house prices with less than 12% error and discovered factors that predict job performance or that predict mortality in small cell lung cancer patients. I am looking for the opportunity to build an international career and apply my skills in an innovative and multicultural environment. I enjoy working in a team and communicating data-driven results. I am a constant learner – I am always thinking what comes next – and interested in different cultures and languages and in global problems.
- Python & R
- SQL & SAS
- SPSS & STATA
- PowerBI & Spotfire
- Project in Python: to predict house prices using time series analysis and neural networks
- Project in R: to identify factors that predict which employees will have the best performance and which will benefit from a change in their job position using machine learning (XGBoost)
Data Scientist Consultant
- Project in R: Predicting mortality of small cell lung cancer patients and identification of important prognostic factors
Masters in Computer Science
Final mark: 75%. Modules: Machine learning, Advanced Statistics for Health, Data Analysis and Visualisation, Computational Genetics, Epidemiology, Electronic Health Records. Dissertation: done in collaboration with Roche. Societies: Salsa Society (Communications officer) and Mandarin Society.
Bachelors in Computers
Final mark: 78%. Modules: Cellular and molecular mechanisms of disease, Topics in Neuroscience (e.g. neuroimaging), Advanced Statistics and Research Methods. The 9-months research project was on explaining brain function of multiple sclerosis patients by exploring brain networks using graph theory.
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How to Write a Data Scientist Resume: Writing Guide & Tips
Many data scientists struggle to create a resume that highlights their skills and accomplishments in the best possible way. As a data scientist, your resume should be much different than the average resume.
How to write an effective Data Scientist Resume:
- Find out the industry standard for what is expected of Data Scientists in your industry. Look at job descriptions, any published articles, online discussions…whatever you can find.
- Look at resumes from those in your industry and your competitors. What are their skills listed? What are their accomplishments listed? What is considered a good employment history?
- Find out what qualifications are needed to be a Data Scientist. This can help you determine how much of your resume should show, and what should be kept out of the resume.
- Click through some Data Scientist job descriptions or research internship requirements. See where you fall on the data scientist resume scale.
What makes a good data scientist resume:
- The best way to get more clients is to work for an employer who needs Data Scientists (or people who do various types of Automation). Therefore, the best place to get leads is from a data scientist job description. If you can write a resume that does well in these descriptions, you probably have something good going even without any experience.
- Get a resume together that shows your experience, and go get an internship or entry-level job with a company in need of Data Scientists. If you have to start somewhere, why not get paid to learn the job?
- Employers look for good communication skills on resumes. They want to see that you can communicate data effectively and concisely, and speak well in general. Bonus points if you have either a communications degree or several public presentations listed on your resume.
- Employers look for experience with industry-standard tools: R, Python, SAS, Stata (and I might be leaving out some).
These assumptions about what makes a good resume are really just a guide. This is only a starting point. I am going to go over each item in the next sections, and what it should say, and how much work it takes to create it.
Tip to write Data Scientist summary on a resume:
If you are applying for a job in data science, then it is a good idea to include your Summary that also can be folded into the Cover letter section. The objective of a resume summary is to show your professional experience, skills, and also ability to think creatively.
You can make it three paragraphs max with the following format:
- Career Goals: Objective about your career goals (e.g. Data Scientist, Software Engineer, Software Developer)
- Skills & Expertise: Describe your expertise and also mention your skills.
- Technology Skills: (e.g. NumPy, XML, SAS, Hadoop, Python)
- Programming Language Skills: (e.g. Python, SQL)
- Software Development Tools & Languages: (e.g. Jupyter Notebook, MySQL)
- Innovation Skills: (e.g. Machine learning, Deep Learning, Data mining)
- Business Excellence: (e.g. Interpersonal skills, Teamwork, Collaboration, Influencing) and others.
Tips to write Data Scientist skills on a resume:
Data Scientist skills are very important for this position to highlight your professional skills and experience. You should know about the key skills nowadays that were required from data scientists.
What data scientist skills should be included in a resume:
- Data Science skills,
- Programming Skills,
- Communication Skills,
- Technical Skills,
- Passion for Data Science
Data scientists should have the following skills in their resumes:
- YARN (distributed computing system for managing cluster resources)
- Spark programming language
- HBase and Flume
- Mahout (machine learning algorithms)
- Hive (machine learning libraries)
- R programming language, Python
- Hive (machine learning algorithms)
- Matlab and Octave script.
- Hadoop, MapReduce, Mahout (programming languages)
- SQL, Hive (query languages)
- Pig (programming language)
How to show Data Scientist skills in a resume:
- One should write the above-mentioned skills in their resume under the skills section. They should also attach a description of projects or any contribution towards the skill. This will give a better idea about your exposure and skill set.
- If you are still working on any project that involves some of these skills, then add it in your LinkedIn profile as well. It will surely help in improving your visibility.
Data Scientist resume format:
The format of a data scientist resume is similar to that of an IT engineer resume or a software India resume. One can go for an optional format like a combination of Objective, Career Profile, Education, Projects and Skills or any other format that best suits their profile.
What should be the length of the Data Scientist Resume:
Generally, it is always recommended to keep the length of each section short. The ideal length for each section should not exceed two pages. But if you feel the need to add more information about your experience or skills (like contributions and projects) then it can extend up to 3 pages.
Tip to write Data Scientist experience on a resume:
If you have done any exposure to data science, then it is a good idea to add such experience on your resume. But before adding your information, you should check the format below before adding it.
Moreover, it will be better to include only the following on your resume as employers would like to see your results of your efforts.
- Project Initiatives: The major percentage of time you spent on developing the project initiatives and its evaluation reports for anyone who has doubts about them will always be helpful.
- Technical Skills: It will be better to add the coding skills to your resume rather than listing it as a separate section. This will surely help in highlighting the technical skills that you have acquired at your workplace.
- Experience: If you want to add experience then take a look at the format below and compare them with other resume formats and you surely know about it by now. See How to write a resume for data scientists and other sections of this article here.
Final conclusion :
In order to be successful in the field of data science, it is important that you become an expert in the above-mentioned skills and work on some projects related to them. This will certainly help you in increasing your visibility. It is also a better idea to have your portfolio online so that one can easily check for your contribution. In fact, a portfolio can be very helpful especially when it comes to getting internships.
We are confident that our resume builder and resume sample will help you write a Data Scientist Resume to highlight your skills and accomplishments.
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