Data Analyst

Position Title: Data Analyst

Location: Bangalore, India

Position Required Skills, Knowledge, and Abilities:

• Minimum 3 years of experience.
• Hands-on experience using Microsoft Excel and formulae within.
• Knowledge of different data types and visualization.
• Understanding of reporting structure and different types.
• Good to have basic knowledge of Python and SQL.
• Good in analyzing, logical reasoning, and understanding workflows.
• Strong proficiency in MS Excel is a must. 
• Strong proficiency in programming languages such as Python or R for data manipulation, analysis, and visualization.
• Solid understanding of data analysis techniques, including statistical analysis, machine learning, and data visualization.
• Experience with AI/ML concepts and techniques, such as regression, classification, clustering, and neural networks.
• Familiarity with popular data analysis libraries and frameworks, such as pandas, NumPy, sci-kit-learn, or TensorFlow.
• Proficiency in SQL and experience with relational databases for data querying and manipulation.
• Stay up to date with the latest advancements in AI/ML technologies, data analysis techniques, and industry best practices.
• Document methodologies, processes, and findings to ensure the reproducibility and transparency of data analysis workflows.

Position Education and Experience (required and preferred):

• Bachelor of Engineering, MCA, MSc. Computer Science is mandatory.

Position Responsibilities:

• Create and run SQL queries to fetch data from DB.
• Write scripts to automate data manipulation activities.
• Cleanse the data and ensure data is good for reporting.
• Build reports based on the clients requirements and KPI.
• Present reports to clients, get confirmation and publish the same.
• Analyse and generate insights from the data.
• This role requires a strong understanding of data analysis techniques, experience with AI/ML concepts, and proficiency in programming and data manipulation.
• Analyse complex datasets using statistical techniques, machine learning algorithms, and data visualization tools to derive insights and identify patterns.
• Collect, clean, and preprocess large volumes of data to ensure its suitability for AI/ML model development.