Data Engineer II

Summary:

We are seeking a skilled professional to join our team and contribute to data-driven transformation initiatives. This role involves developing machine learning and statistical solutions to solve complex problems and generate actionable business insights. The ideal candidate will collaborate with various stakeholders to scale ML-powered solutions across the organization.

Responsibilities:

• Lead end-to-end Data Science initiatives, including data exploration, feature engineering, model development, experimentation, deployment, and business impact measurement.
• Develop machine learning, statistical, and decision science solutions to solve complex Finance Operations problems and generate actionable business insights.
• Partner with Finance, Product, Engineering, and Operations stakeholders to drive data-driven transformation, influence strategy, and scale ML-powered solutions across the organization.

Requirements:

• Bachelor's degree in Computer Science, Statistics, Mathematics, Economics, Engineering, or related quantitative field.
• 4 years of Data Science or applied Machine Learning experience.

Required Skills:

• Strong expertise in SQL and Python.
• Hands-on experience developing and deploying machine learning models in production environments.
• Strong understanding of statistical modeling, hypothesis testing, experimentation, forecasting, anomaly detection, and predictive analytics.
• Experience with large-scale data processing using Spark/PySpark.
• Ability to translate ambiguous business problems into analytical and machine learning solutions.
• Strong stakeholder management and communication skills.

Preferred Skills:

• Experience with LLMs, Generative AI, Hugging Face, RAG architectures, and NLP applications.
• Experience building recommendation systems, forecasting models, optimization models, or decision science frameworks.
• Experience with AWS analytics and machine learning services.
• Experience working in Finance, Accounting, Procurement, or Operations domains.
• Experience with model deployment, MLOps, monitoring, and model governance.
• Experience working in a large technology company.
• Experience with Scala, R, or other statistical programming languages.
• A Master's degree or PhD in a quantitative discipline is preferred but not required.
• AWS Machine Learning Certification or equivalent certifications are a plus.

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