Senior Machine Learning Engineer - Client Insights

Senior Machine Learning Engineer – Client Insights

6 years of relevant experience doing modeling and data science work, conducting advanced analytics and building/iterating on real-world production end-to-end models.
2 years experience as a tech lead
Advanced proficiency in scripting languages like Python and querying languages like SQL
Experience with classification, clustering, regression, and time series models.
Experience working with unbalanced data sets and regularization methods.
Experience building models from scratch, iterating, and owning projects end to end.
A BA in a quantitative field, or equivalent experience
You have experience in a highly analytical role in fast-paced environments
You have a knack for details, and making sure things are correct/accurate

Apply statistical and machine learning methods to build customer-facing models.
Work closely with application engineers to operationalize models you’ve built, ensuring they meet rigors for customer usage, including model performance tracking and having mechanisms to retrain models.
Take the initiative to innovate on our current models and apply new methodologies to new and existing problems/projects/products.
Thought leadership around data governance and standardization
Set standards for feature/variable definitions
Produce documents that give visibility into the data pipelines you’ve built.
Partner with engineering and product leads to provide guidance and leadership in roadmap planning.
Anticipate future support and maintenance overhead for the data-driven features and models you’ve built.
Analyze our data sets to help inform product roadmaps.
Devise optimization models to recommend ways to improve fraud and compliance workflows.
Use heuristics, anomaly detection methods, and unsupervised machine learning methods to detect and predict fraud.
Leverage a deep, data-driven understanding of the key drivers and metrics underpinning Alloy’s products and business lines to draw insights and make recommendations that will help the company grow and scale effectively
Conduct bespoke analyses and research for new customer use cases that support future development of data science products.