Data Analysts

Recruit Data Analysts

Data-driven insights have become crucial for businesses across all industries to make informed decisions regarding product introduction, market expansion, investments, and customer targeting or retention. The utilisation of data can also help identify and resolve inefficiencies within an organisation.

In the present-day competitive business environment, data analysts play a pivotal role in evaluating and tracking organisational performance over time. In addition to statistical analysis, data analysts need to translate data into actionable insights to support decision-making. Data analysts should examine, interpret, and present the information in a visually appealing manner to empower organisations to make informed and efficient decisions. They should also be capable of recognising trends and patterns in the available data, estimating the impact of changes, and devising strategies to maximise data potential. The findings of data analysts should be communicated effectively to stakeholders, and meaningful suggestions should be made to enhance organisational performance.

What are the responsibilities of a Data Analyst?

It is evident that businesses are adopting digital technologies and are keen on harnessing their potential for growth. Data has emerged as a valuable commodity of utmost importance in driving this advancement. In recent times, businesses have been relying on big data analytics to make well-informed decisions and to create competitive products and services. Additionally, the global big data analytics industry was valued at USD 37.34 billion in 2018 and is anticipated to grow at a Compound Annual Growth Rate (CAGR) of 12.3% from 2019 to 2027, marking a likely colossal impact on businesses in the future.

The supply of data scientists and data engineers is swiftly rising on a global level, with ample employment opportunities available in various sectors such as banking, insurance, retail, healthcare, IT, and telecommunications. Polls indicate that the United States will have over 2.7 million job openings in the data-related fields by 2020. Furthermore, by 2021, approximately 70% of corporate executives in the United States are expected to have recruited data experts for their companies. As a result, a greater number of individuals are opting to pursue careers in data analytics to enhance their skill set and benefit from the vast industry prospects.

What are the duties and functions of a Data Analyst?

In the role of a data analyst, one is accountable for obtaining and arranging data and utilising it to extract meaningful insights. The duties of a data analyst, as per Stephanie Pham, an analyst at Porter Novelli, may differ based on the particular client project and the type of data involved. Data analysts can be employed in various sectors, such as healthcare providers, retail stores, and fast-food joints. Data analysts can assist businesses in gaining insights into their customers for a better understanding. Data analysts participate in all phases of the analytical process. Data analysts employed remotely may be tasked with instructing others on how to operate the data collection system. Duties of a data analyst may range from establishing an analytical system to sharing insights based on gathered data. The actual functions of a data analyst can vary based on the company’s nature and the extent of data-driven decision-making employed. Generally, the tasks of a data analyst include data acquisition and organisation, drawing valuable conclusions and educating others on data collection system usage, among others.

• Establishing and preserving data systems and databases, and rectifying coding errors and other data-related issues.
• Data is sourced from primary and secondary sources before being transformed into a format that can be comprehended by people and automated systems.
• Using statistical techniques to analyse datasets, we can pinpoint useful trends and patterns that may be beneficial in diagnostic and predictive analytics models. This process provides deeper insights into the data, which can aid in decision-making. Furthermore, this method helps us identify potential areas of refinement, enabling us to enhance the accuracy of our models.
• By highlighting their significance amid regional, national, and global changes that impact their industry and organisation, they can enhance their perception of their position in the bigger picture.
• Developing executive reports that aptly outline trends, patterns, and forecasts using pertinent data.
• By evaluating current systems, processes, and protocols, I can pinpoint areas that could benefit from updates, modifications, and enhancements to maximise efficiency and effectiveness. Collaborating with programmers, engineers, and organisational executives, I recommend requisite system updates and devise data governance policies that ensure secure and compliant systems.
• Thorough documentation will be produced to facilitate stakeholder comprehension of the complete data analysis process and enable them to replicate or reproduce the analysis as needed.

What are the stages to pursue a career as a Data Analyst?

Data analytics is a sought-after profession that provides job opportunities across various sectors. Whether you want to begin your career or switch to a new one, the following steps can assist you in becoming a successful data analyst. First, it is crucial to obtain a sound understanding of data analysis and related technologies. Gain knowledge through various resources such as online courses, books, and blog posts on data modelling, analytics programming, and data visualisation. Second, establish a professional portfolio showcasing your skills and achievements, which includes relevant certifications, project work, and data analysis experience. Third, network with other data professionals by attending events, joining data-centric Meetup groups, and interacting on social media platforms. Finally, ensure that your resume and job applications are tailored to the position that you seek and are up-to-date. Highlight both technical skills and non-technical skills, such as communication, problem-solving, and interpersonal skills. These actions will assist you in obtaining the skills and experience required to become a successful data analyst. With commitment and persistence, you can secure a job in this in-demand field.

• If you are new to the field of data analysis, it is crucial to grasp the fundamentals of the subject. A comprehensive comprehension of the topic can help you decide if this profession is the right fit for you, while also providing the necessary expertise to be job-ready in the market.
• To secure a role in remote data analytics, it is crucial to possess a specific set of skills. Whether you are pursuing a degree programme, pursuing a professional certification or teaching yourself, it is important to evaluate job postings for positions that catch your eye and scrutinise the programming languages and visualisation tools required. This process will ensure that you are adequately prepared for your intended role.
• Acquiring hands-on experience in working with data is the most efficient approach to learn how to derive value from it. To acquire the requisite skills, consider exploring and enrolling in degree programmes or courses that provide real-world projects and data sets. Alternatively, you can develop your own projects utilising publicly available data sets.
• As you continue to hone your data analysis and programming abilities by exploring web-based data sets and participating in classroom projects, be sure to save your outstanding work for your portfolio. Demonstrating your talents and skills to recruiters through a portfolio of your best work can be an excellent way to secure your dream job.
• For data analysts, it is crucial to not only concentrate on the specifics of data analysis but also to retain a firm grasp of communication and presentation abilities. Providing a precise and concise portrayal of the data analysis results to decision-makers and other corporate stakeholders is an important aspect of this occupation. The ability to deliver clear and succinct information, as well as to construct a storyline from facts and figures, is vital in helping organisations make informed, data-driven judgments.
• After obtaining expertise in data manipulation and presenting results, it is time to streamline your resume and initiate your quest for entry-level data analyst jobs. Even if you lack all of the necessary job requirements, do not hesitate to submit your application. Your learning, practical portfolio, and enthusiasm for the position may be equally significant to the job criteria.
• As you contemplate your career progression in a data analyst role, it is crucial to assess what additional qualifications you may require to attain more advanced positions. Obtaining certifications like the Certified Analytics Professional or the Cloudera Certified Associate Data Analyst can enhance your eligibility for higher-paying roles.

Required Skills for Data Analysts

Acquiring the necessary fundamental skills is the first step in obtaining a lucrative career as a Data Analyst. It is crucial to comprehend the distinct aptitudes needed to excel in this role. These abilities include proficiency in analytics software, comprehension of programming languages and databases, and familiarity with statistical analysis. Furthermore, it is vital to possess excellent communication and problem-solving capabilities, as well as a comprehensive understanding of the business environment in which you will be operating. By having a clear understanding of the skills that require development, you can pursue acquiring the essential abilities for a successful career in Data Analysis.

1. Database Applications

   To excel in the field of Data Analysis, having access to both Microsoft Excel and Structured Query Language (SQL) is essential. Excel is a widely used program that is employed in various industries, whereas SQL is designed for processing massive amounts of data, making it indispensable for those specialising in data analytics.

2. Computer Programming Languages

   Becoming proficient in a statistical programming language such as Python or R enables you to manage enormous volumes of data and solve intricate equations. Python and R are among the most popular languages used, but it is recommended that you go through job postings in the role you are interested in to determine which language would be most advantageous for your organisation.

3. Data Visualization

   For data analysts to be effective, they must be capable of presenting their findings in a clear and appealing manner. The ability to create visual representations of data using tools like Tableau, Jupyter Notebook, and Excel can help ensure that your collaborators, superiors, and other stakeholders involved in the project fully comprehend the information being presented.

4. Statistics and Mathematics

   An in-depth understanding of the fundamentals of data tools can be highly advantageous for a data analyst’s career. Having a strong grasp of statistics and mathematics enables analysts to choose the appropriate tools that address specific problems, identify any shortcomings in their data, and correctly interpret the results obtained.

5. Problem-Solving Abilities

   A proficient data analyst must possess a comprehensive understanding of the situation at hand and the queries that need resolving. Additionally, having the ability to recognise patterns or trends that can contribute to valuable revelations is crucial. Critical thinking skills are essential in this role as they enable an analyst to concentrate on the pertinent data, choose the most effective analysis techniques, and identify any potential errors in the work.

6. Communication Skills

   Effective communication is crucial for a data analyst to convey their ideas and concepts to others successfully. Possessing exceptional written and oral communication skills is vital for data analysts to collaborate successfully with colleagues and other stakeholders.

7. Industry Expertise

   Having a comprehensive understanding of your chosen profession provides an advantage in the workplace and can enhance job applications. For those looking to enter a particular field, it is crucial to stay up to date with industry news and its relevant topics. This enables you to become more familiar with the significant issues and advancements in the sector.

Where to Find Remote Data Analyst Jobs?

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Position Description

Job Responsibilities

• Use modern techniques to analyse and extract data and identify growth opportunities.
• Develop, establish and maintain efficient methods for data cleaning and processing.
• Analyse and rectify corrupted data.
• Construct databases, collect data, and devise scripts to establish flexible and scalable data analysis processes.
• Collaborate with management and technical teams to define critical metrics and key performance indicators (KPIs) and comprehend their analytical demands.
• Deliver actionable insights to multiple stakeholders to aid them in making informed decisions.
• Assess numerical data, produce reports, and communicate findings.
• Develop, implement and oversee state-of-the-art data analysis systems to resolve intricate problems.
• Identify and apply data collection and integration logic to ensure optimal performance and scalability of the systems.

Requirements

• A Bachelor’s/Master’s/MA or Ph.D. degree in Business, Mathematics, Economics, Finance, Statistics, Science or Engineering is mandatory.
• Minimum 3 years of work experience as a Data Analyst or Business Analyst is imperative (exceptions may be considered for exceptionally talented candidates).
• Proficiency in data mining, data modelling, segmentation techniques, and constructing database architecture is essential.
• Capability to arrange, scrutinise, and extract data as per company requirements.
• Familiarity with data querying languages (such as SQL) or statistical/mathematical tools (for instance R, SAS, MATLAB)
• Background in applied statistics or experimentation (such as A/B testing) in an industrial setting.
• Proficiency in programming languages and frameworks, including Python, JavaScript, XML, and ETL.
• English language fluency is necessary to collaborate with engineering management.
• Work on a full-time basis (40 hours per week) with a 4-hour time zone difference with US time zones.

Desirable skills

• I have exceptional analytical thinking abilities and am capable of collecting, organising, scrutinising, and disseminating vast quantities of data, assuring its accuracy and precision.
• Competency in technical writing in pertinent areas, including reports, inquiries, and presentations.
• Outstanding interpersonal and collaborative skills.