Chief Data Insights Officer

1 week ago

Vadodara, Gujarat, India beBeeData Full time ₹ 12,00,000 - ₹ 15,00,000
Senior Data Analyst Position

The role of Senior Data Analytics Analyst involves delivering data-driven analytics solutions to support business decision-making. As a key member of the team, you will be responsible for developing and maintaining advanced data analysis capabilities using technologies such as Power BI, Microsoft Fabric, Snowflake, Azure, AWS, Python, SQL, and R.

  1. Job Description:
  • Design and build interactive dashboards and reports using Power BI and Microsoft Fabric.
  • Perform advanced data analysis and visualization 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.
  1. Required Skills and Qualifications:
  • Professional certifications in data analytics and related fields are highly desirable.
  • Strong technical expertise in data analysis, visualization, and machine learning is essential.
  • Experience with cloud-based platforms and data storage solutions is required.
  • Hands-on experience in building and deploying machine learning models is necessary.
  • Ability to work collaboratively with cross-functional teams is vital.
  • Excellent problem-solving and communication skills are essential.
  1. Benefits:
  • Opportunity to work on challenging data analytics projects.
  • Collaborative and dynamic work environment.
  • Continuous learning and professional development opportunities.
  1. Dimensions:

Financial:

  • Contribute to revenue growth through data-driven client solutions.

Non-Financial:

  • Drive adoption of modern analytics tools and practices.
  • Build strong relationships across business units and with external clients.
  1. Environment:
  • Work collaboratively with cross-functional teams.
  • Adapt to changing priorities and deadlines.

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