Data Scientist

Job Title: Data Scientist

Must Have Technical Skills

• Data Science & ML Model Development

  : Design, develop, and deploy Machine Learning , AI and statistical models using Python, PyTorch, R and TensorFlow.

• AI & Gen AI Use Cases

  : Working knowledge of Generative AI and Large Language Model (LLM) technologies on public cloud platforms, utilizing RAG patterns

• Data Exploration & Feature Engineering

  : Conduct exploratory data analysis and prepare datasets using advanced feature engineering techniques.

• End-to-End ML Pipeline Implementation

  : Collaborate with engineering teams to develop scalable ML pipelines and workflows.

• Cloud & Platform Integration

  : Used cloud-native services on AWS like TensorFlow, Bedrock etc along with Dataiku/Databricks/Snowflake, will be added advantage.

• Model Evaluation & Optimization

  : Evaluate model performance using appropriate metrics and continuously optimize them.

• Stakeholder Collaboration

  : Translate business problems into data science use cases and present insights to technical and non-technical stakeholders.

• Working Knowledge

  : Good to have an experience of AIML platforms like Dataiku/ Databricks/Snowflake and Cloude services like AWS/Azure/GCP.

Responsibilities

• Responsible for the design, development, and maintenance of applications and systems, as well as managing the technical infrastructure in the production environment.
• Develop and implement advanced machine learning and deep learning models to automate and transform business processes.
• Create and apply data science models to generate strategic insights, build predictive models, and deploy solutions that align with current industry standards.
• Leverage generative AI models to create synthetic financial data, simulate market scenarios, generate investment ideas, automate post-trade processes, and enhance interactions with stakeholders.
• Work closely with both technical and business teams to solve complex challenges and perform client demos.

Experience Level

Educational Background

Good To Have:

• Understanding of CI/CD tools for ML model deployment.
• Understanding of data governance, data security, and compliance frameworks.
• Knowledge of visualization tools like Power BI, Tableau, or Plotly.