Job Description Our client, a top Fortune 400 company in the FinTech industry, is seeking a ML Engineer to join their Business Risk Platform team. This team provides development and maintenance support for the tools and engines that Risk Ops team use to monitor merchants' processing behavior. The system has a model with rules that flag any merchant accounts that warrant further investigation. They operate in a cloud environment which requires a deep understanding of cloud storage and computing resources and networking capabilities. Security is of utmost importance, and they require systems to be operable by mitigating security and operational risks via regular updates to dependencies, frameworks, and code base, they require keeping a low vulnerability score per quarter. The ML/AI Engineer III will have a strong understanding of data management principles and best practices, experience designing and implementing data pipelines for AI/ML projects, and have in-depth knowledge of cloud platforms (AWS & GCP) for data storage and management. The objective for the first 3-months of the project will be to create their first ML model/pilot which provides suggestions to the business. This requires a strong understanding of creating and retraining models, with someone who has live model production experience and familiarity with multiple data stores, consolidations, cleaning up data, feature engineering, and understanding patterns (which algorithms to test). What youll do  You will design and lead projects end-to-end, architecting innovative and cloud-agnostic data solutions.  Design and implement reliable & scalable AI/ML-powered solutions.  Translate business problems in the financial domain into technical solutions that leverage machine learning.  Design data processing pipelines to efficiently ingest, store, and prepare data for AI/ML training and simulation.  Integrate AI/ML models into existing fintech applications and workflows.  Document architectural decisions, design patterns and best practices.  Design and develop machine learning and deep learning systems.  Running machine learning/artificial intelligence tests and experiments.  Implementing appropriate ML/AI algorithms.  Study and transform data science prototypes.  Research and implement appropriate ML/AI algorithms and tools.  Develop machine learning/AI applications according to requirements.  Select appropriate datasets and data representation methods.  Run machine learning/AI tests and experiments.  Perform statistical analysis and fine-tuning using test results.  Train and retrain systems when necessary.  Extend existing ML/AI libraries and frameworks. 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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Skills and Requirements 4-6 years of ML/AI/Data Engineering experience (at least 2 years in AI/ML focused role)  Deep understanding of cloud storage, computing resources, and networking capabilities (AWS & GCP)  Machine Learning libraries (scikit-learn, XGBoost, LightGBM, TensorFlow, or PyTorch)  SQL for data extraction and sampling and familiar with BigQuery Cloud platform  Python experience for data manipulation (panda, numpy) and visualization (seaborn, matplotlib, plotly)  Experience handling categorical variables, scaling, and encoding techniques (ex: One-Hot Encoding, Target Encoding)  Data science foundations statistics, probability, data pre-processing, outlier handling, missing value treatment, designing/implementing stratified sampling techniques, familiar with correlation analysis, scatterplot matrix generation, and feature interaction studies.  Experience with model evaluation frameworks and deployment pipelines (ex: MLFlow)  Ability to articulate technical knowledge to technical and non-technical individuals and actively communicate to avoid/combat project bottlenecks by providing solutions Experience working with fraud or anomaly detection models  FinTech, SaaS, or relevant technology industry experience null 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 employment opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment without regard to 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 oruniformed service member status, or any other status or characteristic protected by applicable laws, regulations, andordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or the recruiting process, please send a request to HR@insightglobal.com.