Senior Data Scientist - Python / SQL / AWS

Roles and Responsibilities :

Data-Driven Analysis and Model Building :

• Lead and oversee the creation, deployment, and continuous improvement of data models and analytical systems that optimize business operations.
• Utilize advanced machine learning and statistical models to address complex business problems and improve decision-making processes.
• Ensure that 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 (Credit Risk Model)

Ability to program in python / SQL and proven problem solving and debugging skills, familiar with database technologies and tools

Statistical knowledge of standard modelling concepts and techniques : Linear Regression, Classification models(Logistic, Random forest, clustering, Boosting methods), Neural Networks and Ensembles methods

Technical Skill :

Python

SQL

AWS

(ref : hirist.tech)