KPMG Is Hiring 2023 For Data Analyst | Apply Now

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KPMG Is Hiring 2023 For its Data Analyst, KPMG Drive is organizing Off Campus Drive for candidates in Any Batch. In order to apply, candiadtes should have degree in Bachelors/Master’s Degree. If you are interested, Please apply as soon as possible.

Company Name: KPMG

Role: Data Analyst

Location: Across India

Experience: Freshers(0-2)

Qualification: Bachelors/Master’s Degree

Batch: Any Batch

Job Type: Full Time

Salary: Best in Industry

KPMG Is Hiring 2023

Job Description:

  • Lighthouse, KPMG’s Big Data, AI & Analytics practice has deep industry specialization and focuses on solution delivery for Data Engineering, Data Science, Data Visualization, and Process Analytics.

Leica Biosystems Careers 2023

  • As a data scientist you will be responsible for collecting, analyzing, and interpreting complex data sets to derive insights and create actionable recommendations for business decisions. Some key responsibilities and qualification are mentioned below.

Requirements:

  • Strong knowledge of statistics, mathematics, and machine learning algorithms.
  • Proficiency in programming languages such as Python or R for data manipulation and analysis.
  • Experience with data visualization tools and techniques.
  • Familiarity with databases and SQL for data retrieval and management.
  • Ability to understand and work with large and complex datasets.
  • Strong problem-solving and critical-thinking skills.
  • Excellent communication and presentation skills to effectively convey complex findings to non-technical stakeholders.
  • Ability to work independently and in a team environment.
  • Experience in data engineering or software development is a plus.
  • A degree in fields such as data science, computer science, mathematics, or a related discipline is typically required, while a master’s or doctoral degree is often preferred.

Responsibility:

  • Collecting and preprocessing large datasets from multiple sources.
  • Cleaning and filtering data to remove irrelevant or inaccurate information.
  • Conducting exploratory data analysis to identify patterns, trends, and correlations in the data.
  • Developing and implementing statistical models and machine learning algorithms to solve business problems.
  • Creating and maintaining data pipelines and databases for efficient data storage and retrieval.
  • Collaborating with cross-functional teams to understand business objectives and formulate data-driven solutions.
  • Presenting findings and insights to stakeholders in a clear and concise manner.
  • Continuously monitoring and evaluating the performance of data models and algorithms.
  • Staying up to date with emerging data science techniques, tools, and industry trends.

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