Role overview
We are seeking a Data Scientist with experience in banking and finance to join our team. The ideal candidate will have a strong background in statistical analysis, machine learning, and large language models (LLMs), along with the ability to translate business problems into actionable data-driven solutions.
Responsibilities
- Analyze large financial datasets to extract insights and support business decisions.
- Develop, implement, and evaluate machine learning models for 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 solutions.
- Communicate findings through reports, dashboards, and presentations.
- Work with data engineers to ensure data quality and pipeline reliability.
- Statistical analysis,Data analysis/insights and business problem framing
Basic qualifications
- Master’s or PhD in Computer Science, Statistics, Mathematics, or a related field.
- Proven experience as a Data Scientist in banking or a similar domain.
- Proficiency in Python or R and data science libraries (pandas, scikit-learn, TensorFlow, PyTorch).
- Hands-on LLM experience (OpenAI GPT, Llama, etc.), including prompt engineering and fine-tuning.
- Strong understanding of statistics, machine learning, and data mining techniques.
- Experience with visualization tools (Tableau, Power BI).
- Experience with Big Data platforms (Hadoop).
- Strong SQL and relational database skills.
- Excellent problem-solving and communication skills.
- Experience with cloud platforms (AWS, Azure, or GCP) is a plus.
- Exposure to NLP, deep learning, or time series analysis.
- Experience in deploying models to production.
- Knowledge of banking regulatory and compliance requirements.
- Familiarity with MLOps practices and Agile tools (JIRA or Rally).
Benefits
- Discretionary Annual Incentive.
- Comprehensive Medical Coverage: Medical & Health, Dental & Vision, Disability Planning & Insurance, Pet Insurance Plans.
- Family Support: Maternal & Parental Leaves.
- Insurance Options: Auto & Home Insurance, Identity Theft Protection.
- Convenience & Professional Growth: Commuter Benefits & Certification & Training Reimbursement.
- Time Off: Vacation, Time Off, Sick Leave & Holidays.
- Legal & Financial Assistance: Legal Assistance, 401K Plan, Performance Bonus, College Fund, Student Loan Refinancing.
- Salary Range $120,000-$130,000 a year
Tags & focus areas
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