Essential Responsibilities:
- Develop and optimize machine learning models for various applications.
- Preprocess and analyze large datasets to extract meaningful insights.
- Deploy ML solutions into production environments using appropriate tools and frameworks.
- Collaborate with cross-functional teams to integrate ML models into products and services.
- Monitor and evaluate the performance of deployed models.
Expected Qualifications:
- 3+ years relevant experience and a Bachelor’s degree OR Any equivalent combination of education and experience.
- Experience with ML frameworks like TensorFlow, PyTorch, or scikit-learn.
- Familiarity with cloud platforms (AWS, Azure, GCP) and tools for data processing and model deployment.
- Several years of experience in designing, implementing, and deploying machine learning models.
Additional Responsibilities & Preferred Qualifications:
- Advanced degree (Master's or Ph.D.) in a quantitative discipline such as Statistics, Mathematics, Computer Science, Engineering, or a related field.
- Strong knowledge of statistical and machine learning techniques, including but not limited to logistic regression, time-series modeling, random forests, support vector machines, gradient boosting (e.g., XGBoost), and deep learning architectures (e.g., CNNs, RNNs).
- Proficiency in programming and big-data technologies, with hands-on experience in tools such as Python (Scikit-learn, TensorFlow), SQL, Hadoop, and Spark.
- Relevant modeling experience in one or more of the following domains: credit risk scoring, fraud detection, financial forecasting, or marketing analytics - gained through industry or academic research.
- Strong collaboration and communication skills, with the ability to work effectively both independently and as part of a cross-functional team.
- Ability to articulate complex technical concepts clearly to non-technical stakeholders and build constructive working relationships across functions.
Preferred Qualifications
- Experience with Large Language Models (LLMs), Agentic AI, or related generative AI applications.
- Familiarity with model governance, model risk management, or AI regulatory compliance frameworks (e.g., SR 11-7, OCC 2011-12, EU AI Act) is a plus.
Travel Percent:
The total compensation for this practice may include an annual performance bonus (or other incentive compensation, as applicable), equity, and medical, dental, vision, and other benefits. For more information, visit .
The US national annual pay range for this role is $137,500 to $236,500
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