American Express Hiring Analyst - Data Analytics | Apply Now | 0-2 Yrs Experience

Yogi Siddeswara 0

About Company

American Express, a globally trusted financial services provider, has been a pioneer in delivering innovative financial solutions for over 170 years. Known for its focus on customer service and technological advancements, the company offers a range of products including credit cards, charge cards, and travel services. With a strong commitment to employee well-being, American Express stands as an employer of choice worldwide.

Job Details

Company Name: American Express

Website: American Express

Wikipedia: American Express Wiki

Position: Analyst - Data Analytics

Degree Needed: B.E/B.Tech/M.E/M.Tech/MBA

Eligible Batch: 2022/2023/2024

Work Location: Gurgaon, Haryana, or Bengaluru Urban, Karnataka

Experience Level: 0 – 2 Years

Skills Needed

  • Proficiency in Python, R, SAS, Hive, Spark, and SQL
  • Strong analytical and problem-solving skills
  • Understanding of supervised and unsupervised machine learning techniques
  • Effective communication and teamwork abilities
  • Knowledge of big data frameworks and data visualization tools

Job Responsibilities

  • Analyze large datasets to derive business insights
  • Develop predictive models to optimize decisions in risk, fraud, and marketing
  • Collaborate with cross-functional teams to implement data-driven solutions
  • Stay updated on advancements in analytics and machine learning
  • Effectively communicate findings to stakeholders

Relevant Technologies

To enhance your skills for this role, consider these free online courses:

Interview Tips and Tricks

  • Practice commonly asked questions like explaining machine learning projects.
  • Prepare for a mix of technical and behavioral interview rounds.
  • Brush up on coding exercises involving data structures and SQL queries.
  • Explore resources like LeetCode and GeeksforGeeks for preparation.

Company Reviews

Overall Rating: ⭐⭐⭐⭐⭐ (4.5/5)

Pros: Excellent work-life balance, competitive pay, and a supportive work culture.

Cons: Slightly high workload during peak seasons.


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