Data Engineer

Job Description

Join the AWMT AI/ML Team – Drive Innovation in Advice and Wealth Management. We’re looking for passionate AI/ML professionals to help shape the future of Advice and Wealth Management through cutting‑edge technology and data science. As part of our team, you’ll:

• Design, validate, and evolve LLMs and intelligent agents to deliver explainable, trustworthy recommendations in financial advice and portfolio management.
• Collaborate closely with engineers and cross‑functional teams to improve LLM prompting, accuracy, and system reliability.
• Build and train machine learning models that enable hyper‑personalized portfolios while proactively identifying and mitigating risks and anomalies.
• Lead and contribute to groundbreaking Gen AI initiatives, offering strategic guidance and technical expertise from concept to launch.
• Conduct deep‑dive diagnostic, predictive, and prescriptive analytics to support data‑driven decision‑making.
• Develop alternative modeling approaches to tackle complex challenges and push the boundaries of our capabilities.
• Mentor and support junior data scientists and analysts, fostering a culture of growth and innovation.

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances.

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Leads the execution of large scale, more complex analytics projects. Applies significant quality control and risk assessment of the model, methodologies, outputs, and processes for major data science projects.

Leads and executes deep dive diagnostic, predictive, and prescriptive analytics to support data‑driven business decision making. Creates alternative model approaches to assess complex model design and advance future capabilities. Mentors and develops junior data scientists and analysts.

Identifies and diagnoses data inconsistencies and errors, documents data assumptions, and forages to fill data gaps.

Engages with senior leadership to understand and probe business processes in order to develop hypotheses. Brings structure to requests and translates requirements into an analytic approach.

Guides test design, research design, and model validation. Provides statistical consultation services. Serves as the analytics expert on cross‑functional teams.