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- Tasks: Join our team as a Data Analyst, working with large datasets to provide actionable insights.
- Company: Be part of a dynamic social network focused on data-driven decision-making.
- Benefits: Enjoy flexible work options, professional development opportunities, and a collaborative culture.
- Why this job: Make an impact by optimising business processes and enhancing performance through data analysis.
- Qualifications: Bachelor’s degree in a relevant field and proficiency in data analysis tools required.
- Other info: Ideal for detail-oriented individuals passionate about data and problem-solving.
The predicted salary is between 28800 - 48000 £ per year.
We are seeking a motivated and detail-oriented Data Analyst to join our team. The ideal candidate will work with large datasets, interpret trends, and provide actionable insights to support business decision-making. The Data Analyst will be responsible for data gathering, cleansing, processing, and analyzing, as well as presenting findings to stakeholders in a clear and concise manner.
Key Responsibilities:
- Data Collection & Cleaning: Gather, clean, and organize data from various internal and external sources. Ensure the accuracy, integrity, and quality of data before analysis.
- Data Analysis: Use statistical techniques and data analysis tools (e.g., Excel, SQL, Python, R) to interpret data and generate actionable insights. Identify trends, patterns, and anomalies in the data to inform decision-making.
- Reporting: Create regular reports, dashboards, and visualizations to communicate findings to management and other stakeholders. Present complex data in an easily understandable format (charts, graphs, tables, etc.).
- Work closely with cross-functional teams (marketing, sales, finance, etc.) to understand their data needs. Support data-driven strategies to optimize business processes and performance.
- Develop and implement data models and algorithms to improve decision-making processes. Suggest improvements in data collection, storage, and analysis methods to optimize workflows.
- Collaborate with team members and business leaders to understand key performance indicators (KPIs) and provide data support for ongoing initiatives.
Job Requirements:
Key Qualifications:
- Bachelor’s degree in Data Science, Statistics, Mathematics, Computer Science, Economics, or a related field.
- Strong proficiency in data analysis tools (Excel, SQL, Python, R, etc.).
- Experience with data visualization tools such as Tableau, Power BI, or similar.
- Knowledge of statistical methods and techniques.
- Familiarity with database management and data warehousing.
- Strong communication skills with the ability to explain technical findings to non-technical stakeholders.
- Detail-oriented with a strong analytical mindset.
- Ability to work independently as well as part of a team.
Preferred Qualifications:
- Advanced degree (Master's or higher) in a related field.
- Experience with machine learning models and predictive analytics.
- Knowledge of cloud platforms (AWS, Google Cloud, Azure) is a plus.
Soft Skills:
- Problem-solving mindset.
- Strong attention to detail and a passion for working with data.
- Ability to adapt to new tools, technologies, and processes.
- Strong organizational and time-management skills.
Data Analyst employer: Avua International Pvt. Ltd.
Contact Detail:
Avua International Pvt. Ltd. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Analyst
✨Tip Number 1
Familiarise yourself with the specific data analysis tools mentioned in the job description, such as Excel, SQL, Python, and R. Consider taking online courses or tutorials to sharpen your skills in these areas, as practical knowledge will set you apart from other candidates.
✨Tip Number 2
Build a portfolio showcasing your data analysis projects. Include examples of data cleaning, analysis, and visualisation that demonstrate your ability to derive actionable insights. This will give potential employers a tangible sense of your capabilities.
✨Tip Number 3
Network with professionals in the data analysis field. Attend industry meetups, webinars, or workshops to connect with others and learn about the latest trends and tools. This can also lead to valuable referrals when applying for positions.
✨Tip Number 4
Prepare to discuss how you've used data to influence decision-making in previous roles or projects. Be ready to share specific examples during interviews, as this demonstrates your understanding of the business impact of data analysis.
We think you need these skills to ace Data Analyst
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience and skills that align with the Data Analyst role. Emphasise your proficiency in data analysis tools like Excel, SQL, Python, and any experience with data visualisation tools such as Tableau or Power BI.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for data analysis and your problem-solving mindset. Mention specific projects where you've successfully gathered, cleaned, and analysed data, and how your insights led to actionable business decisions.
Showcase Your Technical Skills: In your application, include examples of your technical skills. If you have experience with machine learning models or cloud platforms, make sure to mention these as they are preferred qualifications for the role.
Prepare for Potential Questions: Think about how you would explain complex data findings to non-technical stakeholders. Be ready to discuss your analytical mindset and how you approach data-driven strategies during potential interviews.
How to prepare for a job interview at Avua International Pvt. Ltd.
✨Showcase Your Technical Skills
Be prepared to discuss your proficiency in data analysis tools like Excel, SQL, Python, and R. Bring examples of past projects where you used these tools to derive insights from data, as this will demonstrate your hands-on experience.
✨Prepare for Data Interpretation Questions
Expect questions that assess your ability to interpret data trends and patterns. Practice explaining complex data findings in simple terms, as you'll need to communicate effectively with non-technical stakeholders.
✨Demonstrate Your Problem-Solving Skills
Think of specific instances where you've tackled data-related challenges. Be ready to discuss your approach to problem-solving and how you used data to inform decisions or improve processes.
✨Familiarise Yourself with the Company’s Data Needs
Research the company and its industry to understand their data requirements. This will help you tailor your responses to show how your skills can directly support their business objectives and enhance their data-driven strategies.
