Amex Hiring Analyst Data Analytics Job| 2024 Apply Now

• Job Title: Analyst Data Analytics
• Salary: Not Disclosed
• Location: Gurugram
• Company: American Express (Amex)
• Qualifications: Graduate
• Experience: 1 – 5 years

ABOUT AMERICAN EXPRESS (AMEX)

American Express (Amex) is a worldwide monetary services employer recognized for its premium rate and credit playing cards, travel offerings, and payment solutions. Founded in 1850, Amex has built a strong popularity for customer support and innovation. Headquartered in New York City, the organization serves millions of customers worldwide, offering several economic merchandise tailor-made to individual and commercial enterprise wishes.

Amex is mainly identified for its travel-associated offerings, inclusive of rewards applications that permit cardholders to earn factors for journey purchases. The business enterprise emphasizes a strong commitment to security, leveraging advanced technology to guard transactions and client information.

In addition to its customer services, American Express also helps companies with various gear to manage expenses, streamline bills, and get entry to financing. The emblem is synonymous with exclusivity and top-rate studies, positioning itself as a pacesetter within the monetary enterprise. Its dedication to customer pleasure and corporate obligation keeps forcing its achievement and boom.

Job Overview 

An Analyst Data Analytics is responsible for collecting, processing, and studying statistics to derive actionable insights that aid enterprise choice-making. This role entails the usage of statistical methods and tools to interpret complicated datasets, perceive traits, and create visualizations. Analysts collaborate with go-purposeful groups to apprehend business desires and communicate findings efficaciously. Key skills consist of proficiency in information evaluation software programs (inclusive of SQL, Python, or R), robust analytical questioning, and attention to detail. The position calls for a blend of technical understanding and commercial enterprise acumen to drive statistics-pushed techniques.

Requirements and Skills for an Analyst Data Analytics:

Educational Background

• Bachelor’s Degree: A diploma in Data Science, Statistics, Mathematics, Computer Science, or an associated subject is commonly required.
• Certifications: Relevant certifications (e.g., Certified Analytics Professional, Google Data Analytics Certificate) can decorate qualifications and demonstrate knowledge.

Technical Skills

• Data Manipulation Tools: Proficiency in records manipulation languages which include SQL for querying databases is crucial. Knowledge of statistics wrangling strategies using equipment like Pandas (Python) or dplyr (R) is likewise useful.
• Statistical Analysis: A strong basis in statistical ideas and methodologies is crucial for reading datasets and drawing meaningful conclusions.
• Programming Skills: Familiarity with programming languages such as Python or R enables analysts to perform complicated analyses and automate duties.
• Data Visualization: Experience with visualization equipment (e.g., Tableau, Power BI, or Matplotlib) helps in creating compelling visible representations of statistics for stakeholder shows.
• Spreadsheet Proficiency: Advanced talents in Microsoft Excel or Google Sheets for facts analysis and reporting are frequently required.

Analytical Skills

• Critical Thinking: Ability to method statistics with a wandering mindset and identify patterns, anomalies, and insights.
• Problem-Solving: Strong problem-solving skills to deal with enterprise challenges and the usage of facts-pushed tactics.

Soft Skills

• Communication: Excellent verbal and written communique talents are critical for translating complicated findings into understandable phrases for non-technical stakeholders.
• Collaboration: Ability to paint effectively in teams, often taking part with numerous departments (e.g., advertising, finance, and IT) to align data insights with business goals.
• Attention to Detail: A meticulous approach to facts analysis to ensure accuracy and reliability in findings.

Experience

• Relevant Work Experience: Prior revel in in information analytics, business intelligence, or associated fields is regularly preferred.
• Project Management: Familiarity with assignment control concepts can be an asset, as analysts frequently manage more than one project and cut-off dates.

Continuous Learning

• Adaptability: Willingness to analyze new tools, technology, and methodologies as the field of statistics analytics is constantly evolving.
• Networking: Engaging with professional communities and attending workshops or conferences can offer ongoing education and networking possibilities.

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