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About the Role
As a Data Scientist, you will own model development for defined financial crime use cases, from understanding client requirements and preparing data to building, evaluating, and deploying models into client workflows. You will work on challenges such as imbalanced alerts, model drift, and explainability while partnering with client compliance, risk, and technology teams. You will also apply NLP, classification, and LLM-based approaches where they improve outcomes, and communicate results through workshops, pilots, and client presentations. This is a hands-on role where you will own assigned use cases end-to-end, exercise sound judgment on model performance and risk, and help junior data scientists grow.
Responsibilities
- Own model development, building, evaluating, and deploying models for assigned financial crime use cases.
- Analyze large datasets, prepare features, and apply statistical and machine learning methods to solve business problems.
- Address imbalanced alerts, model drift, explainability, and performance issues through rigorous evaluation.
- Build NLP and classification solutions, including LLM based text analysis, validating outputs for accuracy, explainability, and business relevance.
- Use explainability methods such as SHAP and LIME to interpret and communicate model behavior, results, and limitations.
- Partner with client compliance, risk, and technology teams, as well as Data Engineering and delivery teams, on requirements, workshops, pilots, and production integration.
- Support model deployment, monitoring, and integration for successful pilot to production transitions.
- Mentor junior data scientists and share practical modeling, evaluation, and delivery practices.
Requirements
- 3 to 7 years of data science or machine learning experience.
- 2 or more years of experience in financial services.
- Strong model building and evaluation skills for financial services use cases.
- Solid grounding in statistics and machine learning.
- Strong Python skills with practical experience using Pandas, NumPy, scikit-learn, or similar tools in production quality work.
- SQL and database experience with Oracle, DB2, SQL Server, Postgres, or similar platforms.
- Explainability experience using methods such as SHAP and LIME to interpret and communicate model outputs.
- Financial crime domain knowledge across AML, fraud, compliance workflows, or related areas.
- Client-facing communication skills, including leading workshops and presenting technical findings.
- Delivery experience, having delivered at least one model into a client workflow.
- Ability to own a use case from requirements through pilot delivery.
- An ownership mindset, knowing when to resolve challenges independently and when to escalate decisions.
Skills
- Python
- Pandas
- NumPy
- scikit-learn
- SQL
- Oracle
- DB2
- SQL Server
- Postgres
- SHAP
- LIME
- AML
- Fraud detection
- Compliance workflows
- NLP
- Classification models
- LLM based text analysis
- Vector databases
- Retrieval components
- KYC
- FATCA
- CRS
- Spark
- Orchestration tools
- Kubernetes
- Kubeflow
- Dask
- RAPIDS
- Model deployment
- Model monitoring
- Data pipelines
- Mentoring junior data scientists
- AI for financial crime detection
- Explainability
- Responsible human oversight
Location
- Hybrid
Work Type
- Hybrid
- Full-time
Experience Level
- 3-7 years of data science or machine learning experience
- 2+ years in financial services
Education Level
- Master’s degree in a quantitative field such as computer science, mathematics, statistics, engineering, or physics.
About the Company
- SymphonyAI Financial Services is on a mission to make the financial system safer.
- We combine more than 25 years of financial crime expertise with advanced AI to help financial institutions detect risk, fight financial crime, and navigate an increasingly complex regulatory environment.
- We are reimagining financial crime compliance around connected risk intelligence, agent led workflows, and embedded governance, helping institutions strengthen controls, reduce manual effort, and adapt as risks evolve.
- SymphonyAI is building the leading enterprise AI SaaS company for digital transformation across the most critical and resilient growth industries, including retail, consumer packaged goods, financial crime prevention, manufacturing, media, and IT service management.
- Since its founding in 2017, SymphonyAI today serves 1500+ Enterprise customers globally and has grown to 3,000 talented leaders, data scientists, and other professionals across over 30 countries.
Equal Opportunity
- We are committed to building a diverse and inclusive team and encourage candidates from all backgrounds to apply.