EXECUTIVE SUMMARY OF RESPONSIBILITIES

The Machine Learning (ME) Engineer will help shape business strategy and product development decisions through data-driven insights. They will make a direct impact on engineering, risk, product, and revenue strategy of Lendistry. Success in this role hinges on your technical aptitude, quantitative abilities, and business acumen: you know how to plow through data with SQL/Python/R, surface insights using math/statistics/ML techniques, and measure the business impact using efficiency/conversion/profit metrics. Some travel may be required.

ABOUT LENDISTRY

Lendistry is the country’s largest minority-led and technology-enabled small business and commercial real estate lender with Community Development Financial Institution (CDFI) and Community Development Entity (CDE) certification. We are a national employer whose mission is to provide economic opportunities and progressive growth for small business owners and their underserved communities as a source of financing and financial education.

GENERAL RESPONSIBILITIES

• Regular attendance during business hours and reliable punctuality are essential functions of this position, and conformance with Lendistry’s attendance policy is a key responsibility of the employee.
• Supports the analytics department by leveraging data technologies to aggregate and structure data, perform statistical analysis, build algorithmic solutions, and
• Mine and analyze massive amounts of unique internal and external data to gain deep business knowledge and insight on customer activity and usage behaviors and their relationships with sales, payment, credit risks, and other types of behaviors.
• Acts as the technical owner of projects that may require significant customization of existing analytic tools, techniques, processes, or development of new ones.
• Perform statistical data analysis and understanding, ensure data quality, and develop tracking and reporting systems to determine the effectiveness of models, rules, and other risk initiatives and programs.
• Design and create systems to structure, aggregate, and turn petabytes of messy information into statistically significant features for modeling purposes.

PROFICIENCIES

• Excellent verbal and written communication skills.
• Strong knowledge of 1 or more scripting and programming languages (Python, Java, SQL, etc.).
• Background in a variety modeling technique: GBM, logistic regression, clustering.
• Experience building, finetune and running inference on transformer models, preferably multi models like LayoutLM.
• Ability to create, sanitize and evaluate Apache arrow datasets from relation tables.
• Ability to create and monitor metrics like data drift, F1 score to evaluate model performance in production.
• Curiosity to try out new models like LLMs on business document corpus.
• Ability to think creatively and innovatively.
• Ability to react proactivity and sense of timeline urgency.
• Good interpersonal skills with the ability to work effectively with individuals and groups at all organizational levels, ability to work independently and as part of a team.

EDUCATION AND EXPERIENCE

• MS/PHD degree in a quantitative field: engineering, math, computer science, statistics etc.
• 3+ years of experience in business analysis, customer segmentation, and/or predictive modeling, preferably in the financial services industry.
• 2+ years in using machine learning packages such as Python, R, SAS.

SALARY

• $131,700 - $179,100/Annually, depending on experience and location

Equal Opportunity Employer/Protected Veterans/Individuals with Disabilities

The contractor will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) consistent with the contractor’s legal duty to furnish information. 41 CFR 60-1.35(c)