Data Analyst

2 weeks ago

Abu Dhabi, Abu Dhabi, United Arab Emirates Agoda Full time
Roles and responsibilities

A DataAnalyst is responsible for collecting, processing,analyzing, and interpreting large datasets to help organizationsmake informed decisions. The role is pivotal in turning raw datainto actionable insights, often focusing on identifying patterns,trends, and key metrics that support business strategies,operations, and growth. Data Analysts use a combination ofstatistical methods, data visualization techniques, and analyticaltools to process data and communicate their findingseffectively.

Here's a detailedbreakdown of the key skills, responsibilities, and qualificationstypically required for a DataAnalyst:

Key Skillsfor a DataAnalyst

  1. DataCollection andCleaning:

    • DataExtraction: Extracting data from various sources,such as databases, spreadsheets, APIs, and websing.
    • DataCleaning: Removing errors, duplicates, andinconsistencies in the data to ensure high-quality, usabledatasets.

  2. Statisticaland AnalyticalSkills:

    • StatisticalAnalysis: Proficiency in performing statisticalanalysis to identify patterns, correlations, and trends indata.
    • DataModeling: Creating models to predict future trendsand behaviors using historicaldata.

  3. SQLand DatabaseManagement:

    • SQL(Structured Query Language): Proficiency in queryingrelational databases (e.g., MySQL, PostgreSQL, SQL Server) toextract and manipulatedata.
    • DatabaseManagement: Understanding how databases work andbeing able to manage, organize, and optimize them for efficientquerying.

  4. DataVisualization:

    • DataVisualization Tools: Creating clear and effectivevisual representations of data using tools such asTableau, PowerBI, or Google DataStudio.
    • Charts andGraphs: Designing charts, graphs, and dashboards topresent data insights in a visually appealing andeasy-to-understandmanner.

  5. Exceland SpreadsheetManagement:

    • Expertisein using Excel for data analysis,including pivot tables, VLOOKUP, macros, and advancedformulas.
    • Handling large datasets andperforming complex calculations in Excelefficiently.

  6. ProgrammingSkills:

    • Pythonor R: Knowledge of programming languages such asPython or R for performing data manipulation, statistical analysis,and automation of data processingtasks.
    • Pandas, NumPy (Python),dplyr (R): Libraries for data analysis in Python andR, used for data manipulation, aggregation, and statisticalanalysis.

  7. BusinessAcumen:

    • Ability tounderstand business processes and translate data insights intoactionable recommendations that align with businessgoals.
    • Knowledge of key performance indicators(KPIs) and metrics relevant to the industry ordepartment.

  8. Problem-Solvingand CriticalThinking:

    • Ability toapproach data analysis challenges with a logical, analyticalmindset to uncover insights.
    • Developingsolutions to address specific business problems based on datafindings.

  9. Communicationand PresentationSkills:

    • Strong writtenand verbal communication skills to present data findings tonon-technical stakeholders.
    • Ability to explaincomplex data insights in simple, understandable terms fordecision-makers.

SoftSkills

  1. Attentionto Detail:

    • Ensuringaccuracy in data analysis, especially when dealing with largedatasets, to avoid errors and ensure reliableinsights.
    • Thoroughly checking data forinconsistencies, missing values, andoutliers.

  2. TimeManagement:

    • Managingmultiple tasks and deadlines effectively, balancing the need forthorough analysis with the need for timelyreporting.
    • Prioritizing tasks based on thebusiness needs and urgency of datarequests.

  3. Collaborationand Teamwork:

    • Workingclosely with other teams, such as marketing, finance, product, andoperations, to gather data and provideinsights.
    • Collaborating with senior analysts ormanagers to refine analysis techniques orapproaches.

  4. Curiosityand ContinuousLearning:

    • A naturalcuriosity to understand how data can drive better decision-makingand improve processes.
    • Staying updated with thelatest data analysis techniques, tools, and industry trends tocontinuously improve yourskillset.
Desired candidate profile
  • Search: Experiment with text ads, bidding, andcampaign structures on Google, Bing, Baidu, Naver, and other searchengines. Adapt to new product features and roll out changes fromsuccessful tests
  • Display: Test, analyze, andoptimize campaigns on Facebook, Twitter, Instagram, andothers
  • Modeling: Analyze the vast amounts ofdata generated by experiments, develop models we can use foroptimization, and build dashboards for account managers

What you'llNeed to Succeed:

  • Bachelor's Degree or higherfrom top university in a quantitative subject (computer science,mathematics, engineering, statistics orscience)
  • Ability to communicate fluently inEnglish
  • Exposure to one or more data analysispackages or databases, e.g., SAS, R, SPSS, Python, VBA, SQL,Tableau
  • Good numerical reasoningskills
  • Proficiency inExcel
  • Intellectual curiosity and analyticalskills
Key Skills
Data Processing,Data Analysis andReporting,Data Analytics
Employment Type: Full-time
Department / FunctionalArea: Data Analysis
Experience: years
Gender: Male
Vacancy: 1

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