“I am really fascinated by data science, and I’m trying to find a data science job that will allow me to build cutting edge data science products and solutions. But, I was wondering, what does a data scientist exactly do? I’m a bit confused because I have been looking at various data science jobs, but they differ based on companies. Some data scientist job descriptions require advanced knowledge of machine learning algorithms while others require strong analytical and programming skills.” This is the most common thought haunting most aspiring data scientists as they upskill themselves for a data scientist career.
In this blog, let’s dig deeper into a data scientist job description template to understand what data scientists really do, what their roles and responsibilities and the skills they need to become successful.
Data Scientist Job Description – Why it varies?
The reason that you are finding conflicting data scientist job descriptions is probably because “data science” by itself is a vast discipline by nature, and encompasses different data science job roles. There are several data science job roles that one can draw up based on the deliverables they create. For example, one type of data scientist job description would mention the need to create output for humans to consume such as product or strategy recommendation while the other kind of a data scientist job description would mention the need to create output for machine to consume such as training data, machine learning models, and algorithms. There are few people who excel at both while others might be drawn to working only in a single direction. However, any data science job role appeals to similar foundational skills and personalities. “Data scientist” is often a blanket title to describe data science jobs that are drastically different but require same foundational data science skills. Not all data scientist job descriptions are created equal. Today, data science job descriptions come in multiple flavours and strengths that suit different types of organizations depending on the kind of problem or projects they are working on. Not to say that one kind of a data scientist is better or worse than other – it all depends on what a company is looking for. But before looking into a data scientist job description template, let’s understand what a data scientist actually does.
What Does a Data Scientist Do?
A data scientist’s job is to glean meaningful insights from data. Raw data can rarely be utilized reliably and that’s the reason enterprises in a variety of industries look to these technical experts to gather, clean, validate, and analyse data. Such a person proactively fetches information from various sources and analyses it for understanding business trends. This requires data scientists to possess a unique blend of skills – math, statistics, programming, machine learning, and visualization. The roles and responsibilities of a data scientist may vary according to the industry and also includes experimental frameworks for machine learning and product development.
Now onto the various sections of a data scientist job description template –
Understanding Data Scientist Job Titles
A great data science job title includes a general term (such as Data Scientist, Junior Data Scientist, Senior Data Scientist, Lead Data Scientist, or Research Analyst ), level of experience , and specializations if any. The general term in a data scientist job title helps professionals search for jobs of the same nature. The level of experience is a clear indicator of the kind of qualified applicants a company is looking for- this is outlined by the amount of responsibilities and prior knowledge needed. And if the company needs professionals with specific specialization say SAS for example then the specialization is often included in the job title something like -Data Scientist (with SAS proficiency) .
Here’s a sample Lead Data Scientist Job Description with Job Title as Senior Principal Data Scientist or Lead Data Scientist –
Data Scientist Job Summary
The second most important section of a data scientist job description is the compelling summary of the position that highlights the data scientists role within the company. It outlines the expectations for the position by mentioning the job duties and requirements. This helps job seekers identify if they are qualified for a particular data science job opening, or not. Make sure your data science resume summary/objective is customized according to the job summary. It should entice the recruiter to surely want to learn more about your professional story. Adding even minute details in the resume summary in accordance to the job summary would definitely impress the recruiter. The resume summary should show your motivation and passion on why you are the best fit for the data science job you are applying for.
Here’s an example of an Amazon Data Scientist Job Description with the Job Summary –
Say for instance,you are to apply for this Amazon Data Scientist job but don’t have enough experience. Your resume summary should flaunt your passion and skill to land the job, something like –
Junior Data Scientist with strong AWS background and 2+ years of experience working on freelance machine learning projects.Involved in AWS community and passionate about solving real-world business challenges using machine learning.
Data Scientist Roles and Responsibilities
This is the most important section of the data scientist job description as it outlines the functions this particular data science job position will perform on a day-to-day basis, how the job functions in the company and who the position reports to. The professional work experience on your data science resume should relate to the roles and responsibilities of the job you are applying to. In case you have relevant work experience to the data science job you are applying for, ensure to highlight such responsibilities through accomplishments rather than responsibilities. Often most professionals mention what they did as data scientists/analysts in their previous organization but do not explain the impact of their duties in the context of business metrics. A good data science resume should highlight the roles and responsibilities of the data scientist job description through cause-effect points so as to give the recruiter an assurance that you are capable of producing real-business outcomes.
If your current work experience does not relate to the data science job you’re applying for , just include the name of the company, the dates worked , and the job title. Don’t fill up the space on your resume with details of irrelevant roles and responsibilities.
Here’s an example of an Amazon Data Scientist Job Description with the Roles and Responsibilities –
When applying for the above job, your resume should highlight your experience working with various machine learning algorithms and Tableau for data visualization, something like –
- Leveraged 300M+ tweets for sentiment analysis that helped improve sales and marketing strategies.
- Applied various regression based machine learning techniques to develop dynamic pricing models and maximize revenue.
- Used Tableau to create real-time ROI graphs that helped the team focus on high-profit business resulting in 25% increase in overall revenue.
Data Scientist Qualification and Skills
Last but not the least the section that every job seeker needs to have an eye to detail for – the preferred and required data science skills for the job. This section of the data scientist job description includes -educational qualifications, level of experience, technical and non-technical skills, and certifications. Most of the data science job descriptions also mention about the personality traits and soft skills needed for the position under this section. A good data science resume should mention about the educational qualifications, the technical skills and other soft skills that are a must-have for the data scientist job you are applying.
Here’s an example of Walmart Data Scientist Job Description with the required and preferred data science skills –
Say if you were to apply for the above Walmart data science job, even job seekers without a PhD or MS are eligible for it. No matter whatever your educational qualification is , mention about the same as it is a necessity and not an optional section. If you have skills like SciKit-Learn, SciPy, NumPy ,include them in a separate section of technical skills as these are among the most preferred skills for the job. Only list the technical skills and tools under this section like – Python, Machine Learning, R, Tableau, and more. Remember to list only those technical skills on the resume that you can speak to. If you once read a book on Python programming but haven’t yet coded in Python, do not list it as one of your data science skills.
The Next Step – Focus on the Data Science Skills That Matter
Hoping that this gives you a sense of how broad a data scientist title is. With so many data scientist job titles floating on the Internet, there is a lot more opportunity for a data scientist. Various organizations are looking for various skill sets, experience levels, and expertise. Figure out what you are passionate about be it statistics, math, programming, or machine learning and enjoy doing it. Also make sure you do thorough research into data science job openings and career growth opportunities before you choose a focus.
As you search for your dream data scientist job, ensure that you look closely at the job description, to find a company and role that best suits your experience and skills. Don’t forget to tailor your resume to each data science job you are applying for as this way you can position yourself in the best way to get hired.
Regardless of what skills you have or how much experience you have, Springboard has a well-formulated data science program to help you master the data science skills you need to build a career you love.