Data Scientist, Mid-Level – Credit

🔥 0 minutes ago

🇧🇷 Brazil – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

📊 Data Scientist

👻 Ghost score 10%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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ASAAS

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded 2010

💼 Consulting

🏥 Healthcare

🏨 Hospitality

Consulting • Healthcare • Hospitality

ASAAS is a leading producer of 360° virtual tours in virtual reality. The company specializes in creating customized virtual tours, utilizing advanced technologies, including 360° video, drone technology, and interactive features, to enhance business visibility and engagement. With a commitment to quality and customer satisfaction, ASAAS offers immersive experiences for various industries, including schools, hotels, museums, and healthcare facilities, and aims to elevate online presence through innovative virtual solutions.

📋 Description

• Collaborate with Credit teams, including Policy, Analytics, Monitoring, and Collections, as well as Credit Product teams • Independently lead Data Science projects, from defining and scoping the problem with Product/Operations through production deployment • Track business impact and continuously improve solutions • Manage the full model lifecycle: experimentation, validation, deployment, monitoring, and iteration • Define metrics and monitoring routines for data drift and concept drift • Conduct studies, identify patterns, and generate insights to improve the efficiency of Credit operations • Develop and maintain artificial intelligence agents to help Product and Business teams explore data from Credit products • Stay up to date on best practices in applied Data Science and development productivity, including AI-assisted development tools • Evaluate and propose improvements appropriate to the context and delivery quality

🎯 Requirements

• Hands-on experience with statistical inference and applying machine learning models to business problems • Proficiency in SQL, Python, and Spark for processing, manipulating, and analyzing large datasets • Experience deploying machine learning models to production in both live and batch architectures, and keeping them operational • Familiarity with predictive credit risk models (application, behavioral, or collections), credit metrics and KPIs, with a focus on credit cards • Ability to communicate technical results and translate statistical metrics into practical business impact • Familiarity with structured development practices and code version control (Git) • Completed degree or equivalent practical experience in Computer Science, Engineering, Statistics, Mathematics, Physics, or related fields • Preferred: experience with Databricks (Model Serving, Unity Catalog, and Genie Spaces) • Preferred: experience with other credit products, such as Receivables Advances and Loans • Preferred: experience with delinquency risk models and credit card limit assignment models • Preferred: experience with structured hypothesis testing and A/B testing • Preferred: experience with Causal Inference, including Power Analysis, regression with controls, Instrumental Variables, and Bayesian methods • Preferred: experience with MLOps frameworks, especially MLflow and Kedro • Preferred: familiarity with AWS

🏖️ Benefits

• Medical and dental insurance with no copay • Life insurance • Prescription medication assistance • Fitness allowance • Four free therapy or nutritionist sessions per month • Quick massage at headquarters • Flexible meal allowance on a Visa card • Free food at headquarters • Childcare assistance • Parental support program • Extended maternity and paternity leave • In-house training platform • Education assistance covering 70% of undergraduate degree and language tuition, as well as courses and books • Home office allowance • Work equipment • Furniture allowance • Partnership with WOBA for coworking access throughout Brazil • Day off during your birthday month • Happy Hour allowance • Referral bonus for new hires • Annual performance-based bonus • Stock options plan • No dress code