Data Scientist

Job not on LinkedIn

🔥 1 hour ago

🇺🇸 United States – Remote

💵 $135k - $170k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

📊 Data Scientist

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PLACE

WebsiteLinkedInAll Job Openings

201 - 500 employees

Founded 2020

💼 Consulting

🏥 Healthcare

🛡️ Insurance

Consulting • Healthcare • Insurance

PLACE is an all-in-one real estate services and technology platform designed for top teams in any brokerage. It simplifies the process of running a profitable real estate business by providing tools for team owners and agents to grow their teams, boost productivity, retain talent, and improve operations. With over 275 locations across the US and Canada, PLACE also connects clients with top agents to facilitate home buying and selling, enhancing the overall experience with advanced technology and business services.

📋 Description

• Analyze data to support or disprove a thesis, letting evidence guide conclusions over confirmation bias • Select and implement the right tools for each problem, from gradient boosting models to transformer-based approaches • Build, train, test, and validate models — from algorithm selection through hyperparameter tuning and rigorous evaluation • Engineer models into production so they run reliably on real infrastructure, serving real customers • Document models, testing protocols, and decision rationale for the team • Monitor and improve models in production, knowing when to retrain, rebuild, or rethink as data and performance drift • Explore agentic and reasoning systems, helping the team separate what's genuinely useful from hype in semi-autonomous, planning AI • Other duties as assigned or apparent

🎯 Requirements

• Bachelor's degree or equivalent experience • 3+ years of prior work-related experience, including 3–5+ years of hands-on AI experience (LLMs like GPT, Claude, Qwen, or similar; building and deploying ML/DL models in production) • Hands-on experience with PyTorch and/or TensorFlow, scikit-learn, XGBoost, LightGBM, AutoGluon, CatBoost, and experiment tracking (MLflow, Weights & Biases) • Experience with model testing frameworks, evaluation, validation, and documentation • Familiarity with ML pipelines, feature engineering, and model serving patterns (batch, real-time, streaming) • Git and collaborative development practices; working familiarity with Jira, Confluence, Slack, and Jupyter

🏖️ Benefits

• PTO as needed • Comprehensive insurance coverage • 401(k) match • Stock option grants • Stock purchase plan