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EXL is hiring for a Data Analyst job


Position:

  • Marketing Analyst

Company:

  • EXL

Location:

  • Bengaluru, Karnataka, India

Job Type:

  • Full-time

Job Mode:

  • Hybrid

Job Requisition ID:

  • [Not Provided]

Years of Experience:

  • 1 – 5 years in data science, preferably within Banking and Financial Services


Company Description

  • EXL is a leading IT Services and Consulting firm with over 10,001 employees. The company is dedicated to helping businesses transform and optimize their operations through data-driven insights and innovative technology solutions. EXL focuses on collaboration and character, ensuring that partnerships are built on understanding each client's unique needs, culture, and legacy systems. The company leverages its expertise in transformation, data science, and change management to enhance efficiency, improve customer relationships, and drive revenue growth. By focusing on deep industry knowledge and cutting-edge analytics, EXL provides tailored solutions that help businesses gain a competitive edge and achieve sustainable success. For more information, visit www.exlservice.com.

Profile Overview

  • The role involves understanding business requirements and translating them into data analytics problems. The Marketing Analyst will provide business insights and manage the entire project lifecycle, from initial client engagement to final delivery and feedback. Building and maintaining client relationships, as well as effectively communicating analytical solutions, are key components of the role. The individual will work closely with team members to structure problems and utilize various analytical tools and techniques for data analysis. Responsibilities also include identifying relevant data sources, analyzing data trends, and developing innovative statistical and machine learning models.

Qualifications

  • Experience: 1 – 5 years in a data science role, preferably in Banking and Financial Services
  • Education:
    • Preferred: Master’s degree in economics, mathematics, engineering, computer science, operations research, or related fields
    • Acceptable: Bachelor’s degree from top-tier institutions
  • Skills:
    • Excellent problem-solving abilities
    • Strong communication and presentation skills
    • Proficiency in programming and data analysis using Python, Excel, SQL, and/or SAS
    • Experience with exploratory data analysis, feature engineering, data summarization, and pivot tables
    • Understanding of basic statistical techniques (e.g., t-tests, chi-square tests, hypothesis testing, regression analysis)
    • Knowledge of PySpark programming is advantageous
    • Familiarity with machine learning techniques and algorithms (e.g., classification, clustering, Random Forest, GBM, XGBoost)
    • Experience with neural networks and natural language processing is a plus
    • Preference for industry experience over academic or online projects/courses

Responsibilities

  • Client Engagement:
    • Develop a deep understanding of client needs
    • Build and maintain strong client relationships
  • Data Management:
    • Identify and source relevant data sets
    • Analyze data to identify trends and patterns
  • Model Development:
    • Create innovative statistical and machine learning models
  • Solution Communication:
    • Present analytical solutions to senior stakeholders
  • Project Management:
    • Oversee end-to-end project delivery
    • Gather and incorporate client feedback

Additional Information

  • The role demands a proactive individual with a strong analytical mindset and the ability to work collaboratively within a team. Effective communication and presentation skills are essential to convey complex analytical insights to non-technical stakeholders. The Marketing Analyst should be adept at using various analytical tools and techniques to solve business problems and deliver actionable insights. Experience in programming, data analysis, and familiarity with machine learning algorithms will be crucial in performing the job effectively. A preference is given to candidates with practical industry experience, demonstrating the ability to apply theoretical knowledge to real-world business challenges.

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