Advanced Business Analytics Lead

2 weeks ago

Bengaluru, Karnataka, India beBeeData Full time ₹ 12,00,000 - ₹ 15,00,000
Senior Data Scientist Job Description

The Senior Data Scientist is a key role in driving business growth through data-driven decision making. This individual will play a crucial part in creating, deploying, and continuously improving data models and analytical systems that optimize business operations.


This senior-level position requires a deep understanding of advanced machine learning and statistical models to address complex business problems and improve decision-making processes. The ideal candidate will lead and oversee the creation of these models and analyses, ensuring they are reproducible, scalable, and sustainable for long-term use.


Key Responsibilities:
  • Lead and oversee the creation of advanced machine learning and statistical models to address complex business problems and improve decision-making processes.
  • Ensure all models and analyses are reproducible, scalable, and sustainable for long-term use.

Automation of Analytical Processes:
  • Design and build automation tools to streamline data preparation, model training, testing, and deployment, improving overall efficiency.
  • Collaborate with software engineers and other technical teams to implement automation solutions that can be leveraged across the organization.
  • Work towards reducing manual interventions and improving data pipeline processes by integrating automation at various stages of the analysis workflow.

Cross-Team Collaboration for Actionable Insights:
  • Collaborate with different teams (e.g., business units, product teams, operations) to understand their challenges, identify opportunities, and deliver data-driven solutions that offer actionable insights.
  • Provide guidance and mentorship to junior team members, enabling them to extract valuable insights from data and build predictive models.
  • Communicate complex technical results and model findings in a clear and concise manner to non-technical stakeholders, ensuring alignment between technical and business goals.

Data Sourcing and Integration:
  • Work with both internal and external data sources to gather the necessary data for analysis, ensuring its quality, reliability, and relevance to business needs.
  • Evaluate and integrate new data sources that can enhance existing models or contribute to new initiatives.
  • Create efficient processes for managing and cleaning large volumes of data from various sources to make it usable for analysis and model development.

Developing Reliable Solutions:
  • Develop robust, scalable data solutions that support ongoing business analytics efforts, ensuring high availability and accuracy.
  • Create predictive models, statistical analyses, and simulations that help businesses forecast trends, identify patterns, and make informed decisions.
  • Take ownership of the end-to-end lifecycle of data solutions, from initial conception and experimentation to implementation and monitoring of performance.

Requirements:
  • Finance domain knowledge for model building.
  • Ability to program in Python/SQL and proven problem-solving and debugging skills, familiar with database technologies and tools.
  • Statistical knowledge of standard modeling concepts and techniques: Linear Regression, Classification models (Logistic, Random forest, clustering, Boosting methods), Neural Networks, and Ensemble methods.

Technical Skills:
  • Python
  • SQL
  • AWS

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