- Job Role: Analyst Data Analytics
- Salary: Not Disclosed
- Location: Gurugram
- Company: American Express (Amex)
- Qualification: Any Graduate
- Experience: 0 – 3 years
ABOUT AMERICAN EXPRESS (AMEX)
American Express (Amex) is a global financial offerings agency renowned for its revolutionary fee answers. Founded in 1850, Amex provides several services, consisting of credit score cards, rate playing cards, and journey-related offerings. With a robust recognition for customer service, American Express is thought to cater to affluent clients and companies, presenting them with top-rate rewards, financial products, and journey blessings. Its network extends internationally, presenting cardholders access to one-of-a-kind perks, which include airport living room admission, travel coverage, and concierge services.
The corporation additionally presents small enterprise owners with tools for handling bills, prices, and worker advantages. American Express is devoted to fostering innovation within the financial industry, investing in technology to enhance the customer experience. With a focal point on acceptance as true and purchaser satisfaction, American Express has hooked up itself as one of the main monetary institutions globally.
Job Description:
An Analyst in Data Analytics is liable for amassing, reading, and decoding big datasets to offer actionable insights for decision-making. They utilize statistical equipment and programming languages like SQL, Python, and R to perceive tendencies, patterns, and correlations. The function involves creating reviews, dashboards, and visualizations to present findings to stakeholders. Analysts additionally collaborate with pass-useful teams to optimize enterprise processes and power statistics-pushed strategies. Strong problem-solving, conversation, and interest in elements are vital, in addition to know-how in records visualization and database control tools.
Requirements and Skills for an Analyst Data Analytics:
Educational Background
- A bachelor’s degree in Data Analytics, Computer Science, Statistics, Mathematics, Economics, or a related field is usually required. Some employers may additionally select applicants with a master’s diploma for greater superior roles.
Technical Skills
- Data Analysis Tools & Programming Languages: Proficiency in statistical gear and programming languages like SQL, Python, and R is vital for querying databases and acting superior records manipulation and evaluation. Knowledge of Excel is also treasured for simple facts evaluation.
- Data Visualization Tools: Familiarity with visualization tools like Tableau, Power BI, or Google Data Studio is essential for developing clean, impactful reports and dashboards.
- Database Management: Experience with databases such as MySQL, PostgreSQL, MongoDB, or SQL Server is critical for efficiently managing and accessing statistics.
- Statistical Analysis & Machine Learning: Understanding of statistical analysis techniques (e.g., regression evaluation, hypothesis trying out) and some exposure to device studying algorithms (e.g., choice trees, clustering, or neural networks) can be a plus for more superior analytical roles.
Analytical & Problem-Solving Skills
- The ability to extract precious insights from complicated datasets is controllable. A Data Analytics Analyst must be able to assume seriously and offer solutions that clear up commercial enterprise-demanding situations.
- Proficiency in deciphering records styles, developments, and correlations and presenting those findings to non-technical stakeholders is prime.
Attention to Detail
- Data accuracy is crucial in this role. Analysts have to be meticulous in checking their information sources, making sure facts are quality, and identifying errors in evaluation.
Communication Skills
- Strong written and verbal communication abilities are needed to explain technical findings to a non-technical audience and deliver actionable insights certainly.
- Ability to collaborate with groups, including commercial enterprise leaders and IT professionals, to recognize records wishes and present solutions correctly.
Business Acumen
- True information on commercial enterprise operations and goals is important to make certain information analytics is aligned with business enterprise goals.
Project Management
- Organizational and time control skills are essential for coping with more than task tasks ofothere well-timed transport of reports and insights.
Adaptability & Continuous Learning
- As the field of records analytics evolves, staying up to date with the trendy gear, technology, and industry tendencies is crucial. Adaptability to new methodologies and technology is important for long-term success.
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