Data Scientist

This is a fully remote position, open to applicants in United States.

📋 Description

• Design, develop, and assess machine learning, statistical, and predictive models to address intricate business challenges across various departments.

• Utilize contemporary artificial intelligence and machine learning techniques, such as large language models (LLMs), generative AI, and advanced analytics, to streamline processes, improve decision-making, and produce business insights.

• Convert business goals into clearly defined analytical, statistical, and machine learning solutions that yield measurable business value.

• Examine extensive, complex datasets to discover trends, patterns, opportunities, and operational enhancements.

• Collaborate with data engineering, IT, and business teams to create scalable data pipelines and implement machine learning models in production settings.

• Assess data quality, model performance, and limitations of AI systems while ensuring the responsible, ethical, and practical application of predictive models.

• Articulate analytical findings, recommendations, and technical concepts effectively to executive leadership as well as both technical and non-technical stakeholders.

• Build, monitor, and refine predictive models, ensuring consistent performance, accuracy, and reliability through ongoing improvement.

• Keep abreast of emerging technologies, advancements in AI, methodologies in machine learning, and best practices in data science to pinpoint opportunities for innovation.

• Work collaboratively across departments to aid strategic initiatives, business intelligence projects, forecasting, automation, and operational optimization.

• Maintain comprehensive documentation of models, methodologies, assumptions, and development processes to uphold transparency, reproducibility, and governance.

• Assist with ad hoc analytical projects and deliver data-driven recommendations that enhance business performance and operational efficiency.

⛳️ Requirements

• A Bachelor's degree in Mathematics, Data Science, Computer Science, Engineering, Physics, or another quantitative field is required; an advanced degree is preferred.

• A strong technical foundation in statistics, predictive modeling, machine learning algorithms, and programming languages such as Python and SQL.

• Proven experience with modern AI technologies, including deep learning, large language models (LLMs), generative AI, MLOps, or similar machine learning frameworks.

• Experience in developing, deploying, and maintaining machine learning models in production environments.

• Solid understanding of cloud computing platforms and contemporary data science tools and technologies.

• Capability to evaluate model performance, navigate trade-offs between accuracy, interpretability, speed, and risk, and apply sound judgment in uncertain situations.

• Experience conveying complex technical ideas to business leaders and effectively collaborating with cross-functional teams.

• Background in financial services, mortgage lending, or other highly regulated sectors is preferred.

• Familiarity with model governance, model risk management, compliance, or regulatory frameworks is an advantage.

🏝️ Benefits

• Comprehensive health, dental, and vision insurance.

• Generous retirement savings plan with company matching.

• Opportunities for professional development and continuing education.

• Flexible work hours and remote working options.

• A dynamic and inclusive work environment that fosters innovation and collaboration.