Is your business having a difficult time reaching its market? Haven’t established your brand yet? Or are you simply unfamiliar with marketing? Keeping up with the trends is essential if you want your business to succeed. Luckily, data scientists are there to do the grunt work. Data scientists can help you cut down cost in your business operations. Learn more about them and how you can hire one for your company!
Data science is a comprehensive study of the flow of information from huge amounts of data present in an organization’s knowledge archive. Data scientists help you overcome the most common challenges you’ll encounter in building your startup. A data scientist is an expert hired to collect, analyze and interpret enormous amounts of data. The data is used to identify the methods on how to help improve the company’s business operations and gain an advantage over its competitors.
The main purpose of data science is to help you:
- Understand the market of your brand.
- Save money in business operations.
- Know the needs of your brand’s audience.
- Gain knowledge about the industry.
You can also check out this Startup Hustle podcast video where Matt DeCoursey and Matt Watson uncover the secrets of how their guest, SickWeather CEO and Co-Founder Graham Dodge, gather sickness data from social media and make this information available to the public.
Figuring out how to hire data scientists for your company is a waste if you don’t know first the purpose of data science for an organization’s business.
Essential Data Scientist Skills
Before you hire a data scientist, know the important skills or qualities of a good data scientist. The important skills include:
- Machine Learning (ML) – The study of algorithms that computer systems used to perform a specific task efficiently without using direct instructions, relying instead on assumptions and patterns. ML helps a data scientist to solve various problems that are based on major organizational issues.
- Programming – Knowledge of programming languages such as Java, R, Python, C++, and SQL is essential because programming will help a data scientist clean and organize an unstructured set of data.
- Statistics – Data scientists should be familiar with statistical concepts such as distributions, maximum likelihood estimators and statistical tests. Statistics help evaluate and design experiments, and business stakeholders choose the right decisions.
- Non-Technical Skills – Effective communication skills, strong business acumen, analytical and critical thinking, intellectual curiosity, and problem-solving are the most important non-technical skills that a data scientist should have. They allow a data scientist to understand business problems and find a solution for them; communicate with non-technical peers and use them in the most efficient manner.
Basic Steps on How to Hire Data Scientists
If it’s your first time hiring a data scientist for your company, work with your HR department. We recommend the following steps:
- Build a talent pool – Your company should build a pool of prospective job applicants by collecting resumes as early as possible even when you don’t urgently need data scientists. When you only need one or two data scientists for your project, you can select the applicants from the pool with the most extensive qualifications to undergo your assessment process. Then mark the other candidates in the pool as “future pooling” for your future needs. This pool will make it easier for you to call a lot of applicants when the need becomes urgent.
- Define the position requirements – You should ask yourself “What am I looking for in a data scientist candidate?”. The skills you are looking for in a data scientist should match the needs of your business or project. For example, if you need a data scientist who will report to a client and project manager, you will need someone with effective written communication skills such as documentation and report writing, and a communicator who can connect with people from different backgrounds. It’s important that when you post your job ads in recruitment banks, state the required educational level, technical and soft skills, years of work experience, and other qualifications.
- Data scientist interview – Your HR department will screen the applicants from the talent pool and contacts those who will qualify for a series of interviews and assessment exams at the office. Your HR interviewer should ask questions such as “Why are you exploring other job opportunities from other companies?”, “Why are you interested in a career at our company?”, “What can you contribute to our company?”, “What are your short-term and long-term career goals?’, and “What are your salary expectations?”. From these questions, you’ll be able to discern if a candidate will be an asset to your company.
- Know the personality and behavioral traits – It’s important that the interviewees should describe their personality and behavioral traits during the HR interview. In this way, the interviewer determines if they have important non-technical skills such as adjustability, empathy, business insight, how well they can fit in a team, and efficiently do their job with little supervision.
- Technical interview – You can ask one of your senior software developers or development managers to do a technical interview with an applicant if your company doesn’t have any data scientists yet. Ask the applicant about the technical skills that they’ve learned from formal education, training and work, and the specific skills that they’re practicing. If applicable, the interviewer can ask applicants to do an on-the-spot test by writing their answers on a whiteboard to assess their problem-solving abilities and how quickly they can come up with a solution during a pressured situation.
- Assessment exams – Aside from a technical interview, the skills assessment exams will validate the technical and non-technical skills of a data scientist applicant. Your office should have computer-based assessment exams so these can be administered to groups of applicants at the same time. The computer-based exams should be grouped into several categories such as an English proficiency exam, aptitude or Intelligence Quotient exam, essay test, and specific skills tests that are customized for data scientists.
- Selecting the right candidate – After a candidate has passed the series of assessment exams and interviews, it comes down to the final decision. As the company owner, you will decide if the successful candidate is really the best data scientist for your business. You can analyze the results of the interviews and assessment exams, and read the resume and other credentials submitted by the candidate. Then ask yourself questions like “Can this person satisfactorily perform the role?”, “Will this person contribute to my company’s growth?”, and “Can he/she work well with a client or in a team? Make sure you make the right decision to hire the successful candidate because a data scientist’s work can have a critical role in your company’s success.
Remote Teams from Full Scale
Do you want to augment your in-house software development team, but don’t want to hire more in-house staff? Full Scale can help you with your problem! We can provide you with a remote team of software developers to help mobilize your startup. Send us a message to learn more about our services. Also, check out our Guided Development video to get a feel of what Full Scale has in store for you!
