Data scientist
Must Have Technical/Functional Skills
Primary: Artificial intelligence ML LLM
Secondary: Data science Python NLP Agile tools
Experience: 10
Roles & Responsibilities
Experience with NLP deep learning or time series analysis.
Experience deploying models to production environments.
Knowledge of regulatory requirements and compliance in banking and finance.
Familiarity with MLOps practices and tools.
Experience with Agile methodology and tools (JIRA or Rally)
Proven experience as a Data Scientist in Banking or a similar domain
Proficiency in Python or R and experience with data science libraries (e.g. pandas scikit-learn TensorFlow PyTorch).
Hands-on experience with large language models (e.g. OpenAI GPT Llama or similar) including fine-tuning and prompt engineering.
Strong knowledge of statistics machine learning and data mining techniques.
Experience with data visualization tools (e.g. Tableau Power BI).
Experience with Big Data Platforms (Hadoop).
Familiarity with SQL and working with relational databases.
Excellent problem-solving communication and collaboration skills.
Experience with cloud platforms (AWS Azure or GCP) is a plus.
Analyze large financial datasets to extract insights and support business decisions.
Develop implement and evaluate machine learning models and algorithms tailored to banking and finance use cases (e.g. risk modeling fraud detection customer segmentation).
Apply and fine-tune large language models (LLMs) for tasks such as document analysis customer communication and regulatory compliance.
Collaborate with cross-functional teams to understand business requirements and deliver data-driven solutions.
Communicate findings and recommendations through reports dashboards and presentations.
Work with data engineers to ensure data quality and pipeline reliability.
Salary Range- $120000-$135000 a year
Data scientist Must Have Technical/Functional Skills Primary: Artificial intelligence ML LLM Secondary: Data science Python NLP Agile tools Experience: 10 Roles & Responsibilities Experience with NLP deep learning or time series analysis. Experience deploying models to production environments....
Data scientist
Must Have Technical/Functional Skills
Primary: Artificial intelligence ML LLM
Secondary: Data science Python NLP Agile tools
Experience: 10
Roles & Responsibilities
Experience with NLP deep learning or time series analysis.
Experience deploying models to production environments.
Knowledge of regulatory requirements and compliance in banking and finance.
Familiarity with MLOps practices and tools.
Experience with Agile methodology and tools (JIRA or Rally)
Proven experience as a Data Scientist in Banking or a similar domain
Proficiency in Python or R and experience with data science libraries (e.g. pandas scikit-learn TensorFlow PyTorch).
Hands-on experience with large language models (e.g. OpenAI GPT Llama or similar) including fine-tuning and prompt engineering.
Strong knowledge of statistics machine learning and data mining techniques.
Experience with data visualization tools (e.g. Tableau Power BI).
Experience with Big Data Platforms (Hadoop).
Familiarity with SQL and working with relational databases.
Excellent problem-solving communication and collaboration skills.
Experience with cloud platforms (AWS Azure or GCP) is a plus.
Analyze large financial datasets to extract insights and support business decisions.
Develop implement and evaluate machine learning models and algorithms tailored to banking and finance use cases (e.g. risk modeling fraud detection customer segmentation).
Apply and fine-tune large language models (LLMs) for tasks such as document analysis customer communication and regulatory compliance.
Collaborate with cross-functional teams to understand business requirements and deliver data-driven solutions.
Communicate findings and recommendations through reports dashboards and presentations.
Work with data engineers to ensure data quality and pipeline reliability.
Salary Range- $120000-$135000 a year
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