Advanced Analytics Professional

2 days ago

Palakkad, Kerala, India beBeeData Full time ₹ 80,00,000 - ₹ 1,50,00,000
Job Purpose

The Senior Data Analytics Analyst plays a key role in delivering hands-on analytics solutions across the UK and Ireland. This role focuses on bespoke report building, dashboard development, and advanced data analysis using technologies such as Power BI, Microsoft Fabric, Snowflake, Azure, AWS, Python, SQL, and R.

This is an exciting opportunity for experienced analysts to take their skills to the next level and contribute to business growth through data-driven insights.

Key Responsibilities:
  • Design and build interactive dashboards and reports using Power BI and Microsoft Fabric.
  • Perform advanced data analysis and visualisation to support business decision-making.
  • Develop and maintain data pipelines and queries using SQL and Python.
  • Apply data science techniques such as predictive modelling, classification, clustering, and regression to solve business problems and uncover actionable insights.
  • Build, validate, and tune machine learning models using tools such as scikit-learn, TensorFlow, or similar frameworks.
  • Collaborate with stakeholders to translate business questions into data science problems and communicate findings in a clear, actionable manner.
  • Use statistical techniques and hypothesis testing to validate assumptions and support decision-making.
  • Document data science workflows and maintain reproducibility of experiments and models.
Requirements:
  • Strong technical expertise in Power BI, Microsoft Fabric, Snowflake, SQL, Python, and R.
  • Experience with Azure Data Factory, Databricks, Synapse Analytics, and AWS Glue.
  • Hands-on experience in building and deploying machine learning models.
  • Ability to translate complex data into actionable insights.
  • Excellent problem-solving and communication skills.
Judgement Skills:
  • Balances team development with delivery priorities and business needs.
  • Makes informed decisions on technical design, resource allocation, and delivery timelines.
  • Evaluates project outcomes and identifies opportunities for team and process improvement.
  • Encourages experimentation while maintaining delivery discipline and governance.

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