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ADI Recruitment Drive; Hiring Data Analyst – Apply Now


They are looking for a highly analytical and motivated Data Analyst/Data Scientist to join their central data team. As a new college graduate, you will play a key role in supporting their Enterprise Data Platform, analyzing complex datasets, and applying machine learning techniques to solve business problems. This role will provide you with hands-on experience in data analysis, visualization, and predictive modeling, allowing you to make a tangible impact across multiple business units. Candidates are advised to apply soon, before the link expires

Name of the Organization: Analog Devices Inc (ADI)

Requisition ID: R243841

Positions: Data Analyst / Data Scientist

Location: Bangalore

Salary: As per company Norms

Required Qualifications:

  • Bachelor’s degree in Data Science, Statistics, Mathematics, Computer Science, or a related field. 
  • Proficiency in Python, R, and SQL for data manipulation and analysis.
  • Strong foundation in statistics, data analysis, and machine learning concepts.
  • Familiarity with data visualization tools such as Tableau, Power BI, or similar. 
  • Ability to work in a collaborative, cross-functional environment and communicate effectively with both technical and non-technical stakeholders.

Preferred Skills:

  • Experience with machine learning libraries such as scikit-learn, TensorFlow, or PyTorch.
  • Knowledge of data cleaning and transformation techniques.
  • Basic experience with cloud platforms (Azure, AWS, or GCP).
  • Familiarity with big data tools like Spark is a plus.

Responsibilities:

  • Analyze large datasets to generate insights that drive business decisions and strategy.
  • Develop dashboards and reports using tools like Tableau, Power BI, or equivalent.
  • Collaborate with data engineers and business stakeholders to define analytical models and reporting needs.
  • Assist in building and deploying predictive models and machine learning solutions.
  • Perform data cleaning, transformation, and feature engineering to prepare data for analysis.
  • Present findings and insights to key stakeholders through visualizations and reports.
  • Contribute to data-driven initiatives to improve efficiency and decision-making across the company.

 

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