Hire Data Wrangling/Data Science Experts
Data experts and data scientists leverage data to guide organisations towards success. Data wranglers/data science professionals oversee and organise the activities of other team members while managing a variety of data-driven initiatives, depending on the magnitude of the project. They are data analysts who draw upon their technological and social science knowledge to recognise patterns and manage data. To address business challenges, data professionals use their industry experience, understanding of the context, and willingness to challenge existing assumptions.
The increasing popularity of data science has led to a surge in the demand for data wranglers and data scientists. If you are considering entering this field but are unsure of where to start, then this article aims to provide an overview of the systematic techniques, professional knowledge and skills required to secure a successful career as a remote data wrangling and data science expert.
What is the scope of data manipulation/data science?
Data science is having a remarkable impact on our daily lives. For example, the Internet contains an immense number of web pages; a simple Google search yields a staggering 1 billion results. Behind the scenes, a data scientist is combing through this vast array of information to furnish the precise results requested. This illustrates the power of data science in today’s world.
Companies often possess an abundance of data that can be unfamiliar to many people. To make the most of this data, businesses must employ professionals in data wrangling and data science to assess the data and uncover valuable insights. These findings can then be used to inform accurate decisions about how to improve the products and services offered by the company.
What are the duties and obligations of a data wrangling/data science expert?
The following are some of the most crucial tasks after securing remote data wrangling/data science expert employment.
- To address issues, use your understanding of data cleansing, data wrangling, quantitative analysis, and data mining.
- Collaborate with stakeholders to have a deeper knowledge of the demands of the firm.
- Assist in making educated judgments by collecting, analysing, and altering data.
- Reports and dashboards should be created and analysed.
- Manually convert, map, and arrange data for simple consumption.
- Give business analysts trustworthy and actionable data.
- Train statistical models and visualise and aggregate data.
- Provide useful data insights to non-technical clients and stakeholders.
How do you become a data wrangler/data scientist expert?
Despite the comprehensive expertise and competencies required for these programming roles, anyone with a genuine desire to pursue a career in this field and the ability to undertake some of the aforementioned duties can attain a position as a remote data wrangling/data science specialist.
Obtaining the skills needed for data wrangling/data science can be achieved in a variety of ways. One of the most popular options is to pursue a college education; this will provide you with a strong foundation and credentials essential for entering the profession. However, this route can be costly and time-consuming, and those who have not achieved good grades in high school may find themselves unable to attend the college necessary to secure a data wrangling/data science specialist job.
Attending a boot camp program is another viable option for those interested in pursuing a career in remote data wrangling or data science. This option may be advantageous in terms of both cost and time compared to a traditional three- or four-year degree program, depending on the boot camp. Boot camps focus on providing students with the technical skills they need to be competitive in the field, and can be completed either in person or online.
It is without a doubt that whichever path you decide to take in order to become a remote data wrangling/data science specialist, you are sure to have a prosperous career and countless job opportunities ahead of you.
Data wrangling/data science expertise is necessary.
Gaining the requisite skills is the initial step to securing lucrative data wrangling/data science specialist positions. Let us now more closely examine each of these key competencies.
Statistics and mathematicsFor any successful data wrangling/data science specialist, a strong mathematical and statistical background is essential. Organisations that are heavily reliant on data, in particular, need a data wrangling/data science professional to understand various statistical techniques – such as maximum likelihood estimators, distributions and statistical tests – to make informed recommendations and decisions. Additionally, expertise in calculus and linear algebra is indispensable, as most machine learning algorithms are built upon them. Therefore, if you wish to work as a remote data wrangler/data science specialist, you should be proficient in both statistics and mathematics.
Analytics and modellingDue to the fact that the success of data is heavily reliant on the quality of the individuals who analyse and manipulate it, it is essential for applicants for remote data wrangling/data science specialist positions to be highly knowledgeable in this field. A data wrangling/data science expert should be capable of researching data, conducting tests, and creating models in order to uncover new information and anticipate future events. This requires an aptitude for critical thinking and the ability to communicate effectively. Therefore, it is strongly advised that individuals interested in applying for such positions gain an understanding of modelling and analytics prior to submitting their applications.
Machine learning methodsWhile having specialised experience in the field of data wrangling/data science is not a requirement for expert positions, employers typically expect applicants to have at least a basic level of understanding. Going forward, companies will be looking for individuals who have a solid grasp of machine learning techniques such as decision trees, logistic regression, and other relevant components.
ProgrammingIn order to be considered for the highest level of remote data wrangling/data science specialist jobs, it is essential for a candidate to possess strong programming skills. Prospective employers will likely require a strong background in languages such as Python, R, and other relevant object-oriented programming languages. This includes a mastery of the fundamental syntax and functions, flow control statements, libraries, and documentation. Therefore, it is essential to hone these programming skills to have the best chance of success.
Visualisation of dataData visualisation is an integral component of the data wrangling/data science professional’s skill set, allowing them to effectively communicate key points and gain acceptance for proposed solutions. In order to be considered for remote data wrangling/data science positions, a data wrangling/data science professional must be proficient in the ability to break down complex data into more manageable segments, as well as the use of a range of visual aids, such as charts and graphs.
Intellectual curiosityAt the heart of a data scientist’s role is a strong inclination to identify and address problems, particularly those that require out-of-the-box thinking. As data itself is essentially meaningless, a competent data wrangler/data science professional has an innate desire to explore what the data is trying to communicate and how it can be applied to a broader context.
CommunicationDue to the fact that data is unable to communicate unless it has been manipulated, an effective data wrangler/data scientist must possess strong communication skills. Communication plays a critical role in a project’s success, including conveying to the team the steps necessary to transform the data from its current state to the desired result, as well as presenting to stakeholders. Enhancing your communication capabilities can impress potential employers during virtual data wrangling/data science specialist interviews.
Business acumenAs a data wrangler/data scientist, it is essential to have a comprehensive understanding of a company’s goals and objectives, and the ability to design solutions that are both cost-effective and easy to implement. This will enable you to effectively utilise data to benefit the company and ensure that your solutions are widely accepted. To be successful in obtaining a remote data wrangling/data science role, you must be commercially savvy and demonstrate that your solutions are tailored to the company’s objectives.
How can I find remote data wrangling/data science jobs?
After conducting a thorough investigation into the requirements for remote data wrangling and data science specialist positions, it is clear that the most important factor to consider is to put forth your best effort and practice regularly. As the field of data science continues to grow in popularity, new technical advancements are made every day. With an increase in the number of people entering the industry, competition is inevitable. To ensure that you stay ahead of the curve, it is essential to keep up with industry trends and stay abreast of the latest developments. This will allow you to enhance your career and remain competitive in the field.
At Works, we provide the best remote data wrangling/data science expert opportunities to help you achieve your professional goals. You can further hone your skills by collaborating with other talented engineers on complex technical tasks. Join a global network of the most qualified data wrangling/data science experts to find full-time, long-term remote employment with increased remuneration and professional growth.
Responsibilities at work
- Use your knowledge of data cleansing, data wrangling, quantitative analysis, and data mining to your advantage.
- Work with stakeholders to comprehend business needs.
- Gather, philtre, and convert data to aid in making educated choices.
- Create and evaluate dashboards and reports
- Convert, map, and arrange data manually for easy consumption.
- Provide business analysts with reliable and actionable data.
- Perform data visualisation and aggregation, as well as statistical model training
- Inform non-technical customers and stakeholders about actionable data insights.
- Bachelor’s/ Master’s degree in engineering, data/computer science, or information technology (or equivalent experience)
- At least three years of experience as a data scientist/data wrangler is required (rare exceptions for highly skilled developers)
- Knowledge of data transformations such as merging, sorting, and aggregation
- Knowledge of data querying languages such as SQL.
- Knowledge of numerous programming languages, such as Java, R, and Python
- Expertise in statistical analysis, as well as discovery of patterns and anomalies
- Practical experience with algorithms and data structures
- Knowledge of AI concepts, database systems, human/computer interaction, numerical analysis, and software engineering is required.
- Extensive experience evaluating massive datasets to solve challenging challenges
- English fluency is required for good communication.
- Work full-time (40 hours per week) with a 4-hour overlap with US time zones
- Extensive knowledge in transforming raw data into actionable insights
- Working understanding of ETL pipelines, data visualisation, and data aggregation Tools like Parsehub, Scrapy, OpenRefine, and others
- Outstanding analytical and problem-solving abilities
- Excellent interpersonal and communication abilities