Expert Data Insights Specialist

7 days ago

Anand, Gujarat, India beBeeData Full time US$ 90,000 - US$ 1,20,000
Job Title

The company is seeking a highly skilled and experienced Data Analyst to join their team.

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.
  • Perform feature engineering and data preprocessing to prepare datasets for machine learning workflows.
  • Build, validate, and tune machine learning models using tools such as scikit-learn, TensorFlow, or similar frameworks.
  • Deploy models into production environments and monitor their performance over time, ensuring they deliver consistent value.
  • 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.
  • Support the Data Analytics Manager in delivering analytics projects and mentoring junior analysts.

Requirements:

  • Professional Certifications (preferred or in progress):
  • 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.

Benefits:

  • Drive adoption of modern analytics tools and practices.
  • Build strong relationships across business units and with external clients.

Dimensions:

  • Financial: Contributes to revenue growth through data-driven client solutions.
  • Non-Financial: Drives adoption of modern analytics tools and practices.

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