Senior Data Scientist

Job not on LinkedIn

🔥 1 minute ago

🇺🇸 United States – Remote

💵 $175k - $225k / year

⏰ Full Time

🟠 Senior

📊 Data Scientist

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

👻 Ghost score 0%

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.

Apply Now

Find Similar Remote Jobs

Set Up Email Alert For New Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume

Kiavi

WebsiteLinkedInAll Job Openings

201 - 500 employees

Founded 2013

💼 Consulting

🏥 Healthcare

🏗️ Construction

💰 $158M Debt Financing on 2023-01

Consulting • Healthcare • Construction

Kiavi is a technology-driven financial company that provides fast and reliable financing solutions for real estate investors. Specializing in short-term 'fix-and-flip' loans, rental property financing, and new construction loans, Kiavi empowers both emerging and experienced real estate investors by offering competitive rates, high leverage, and efficient processes. With the use of an advanced technology platform, Kiavi simplifies and accelerates the loan application and approval process, allowing investors to manage their investments with ease and confidence. The company operates across multiple states and offers various resources to support investor growth.

📋 Description

• Identify high-impact machine learning and AI opportunities with product, engineering, operations, and business teams • Design, train, fine-tune, and evaluate machine learning and deep-learning models • Work with foundation models across language, vision, and multimodal applications • Develop robust datasets, features, training pipelines, and evaluation frameworks • Run efficient experiments on GPU infrastructure and improve model quality, speed, and cost • Compare modeling approaches and recommend solutions based on empirical results and business impact • Build reusable modeling components, evaluation frameworks, and implementation patterns • Establish interfaces and standards enabling teams to adopt proven AI capabilities • Build reproducible, testable models and supporting systems suitable for production • Partner with ML and software engineers on deployment, monitoring, reliability, and model improvement • Communicate results, limitations, and tradeoffs to technical and non-technical stakeholders • Stay current with machine learning advances and assess their practical value • Turn ambiguous business needs into defined machine learning problems and measurable success criteria • Build models improving customer or operational outcomes • Balance model quality, complexity, latency, reliability, and cost • Create reusable foundations for multiple teams and use cases • Raise technical standards for experimentation, evaluation, and production AI

🎯 Requirements

• Bachelor’s or advanced degree in Computer Science, Machine Learning, Electrical Engineering, Applied Mathematics, or a related technical field, or equivalent practical experience • 5+ years of experience developing machine learning solutions, including taking models beyond initial experimentation • Strong programming and software-engineering skills, particularly in Python • Strong foundations in machine learning, statistics, algorithms, data structures, and experimental design • Hands-on experience with PyTorch or TensorFlow • Experience training or fine-tuning transformer-based, vision, or multimodal models • Experience working with GPUs and understanding practical constraints of model training and inference • Ability to work with large, complex, and imperfect datasets • Ability to own open-ended problems from initial investigation through implementation and measurement • Ability to generalize successful solutions into reusable capabilities rather than one-off models • Strong communication and cross-functional collaboration skills • Preferred: Master’s degree or PhD in Computer Science, Machine Learning, or a related field • Preferred: Experience with distributed training, model optimization, quantization, or parameter-efficient fine-tuning • Preferred: Experience deploying and monitoring machine learning models in production • Preferred: Familiarity with cloud infrastructure, distributed data processing, and modern ML development platforms • Preferred: Experience building AI systems in regulated, risk-sensitive, or high-stakes environments • Preferred: Contributions to applied research, open-source projects, patents, or production AI products

🏖️ Benefits

• Annualized base pay of $175,000–$225,000 • Bonus • Benefits • Remote work arrangement • Secure identity verification process using biometric and device validation • Equal Opportunity Employer • E-Verify used to confirm employment eligibility