Senior Data Scientist

🕒 July 15

🌐 United States, Canada – Remote

🇺🇸 United States – Remote 🇨🇦 Canada – Remote

⏰ Full Time

🟠 Senior

📊 Data Scientist

🦅 H1B Visa Sponsor

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👻 Ghost score 27%

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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Quantiphi

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 2013

💼 Consulting

🏥 Healthcare

📦 Logistics

💰 Series A on 2019-12

Consulting • Healthcare • Logistics

Quantiphi is a leading AI-first digital engineering company that leverages a decade of industry expertise to empower businesses through scalable, secure, and adaptable AI solutions. By integrating cutting-edge technology with real-world applications, Quantiphi transforms organizations across various sectors including healthcare, finance, education, and retail. Their services span AI applications, data analytics, cloud infrastructure modernization, and custom AI implementations. Quantiphi partners with technology giants like AWS, Google Cloud, NVIDIA, and others to drive AI adoption and deliver transformational opportunities for enterprises.

📋 Description

• Lead end-to-end data science initiatives for predictive analytics, including demand forecasting, churn prediction, and risk modeling • Translate business requirements into ML problem statements and define modeling approaches • Design, build, and deploy machine learning models using regression, classification, clustering, and time series techniques • Drive feature engineering, data preparation, and exploratory data analysis to improve model performance • Develop and manage scalable ML pipelines from data ingestion through model deployment • Deploy and manage models on AWS using services such as SageMaker • Ensure model performance through validation, monitoring, and periodic retraining • Collaborate with data engineering and MLOps teams to productionize ML solutions • Apply best practices for model governance, explainability, and responsible AI • Mentor junior data scientists and provide technical leadership while remaining hands-on • Communicate insights, model outputs, and recommendations to business stakeholders

🎯 Requirements

• 8+ years of relevant hands-on technical experience implementing and developing cloud solutions on AWS • Strong experience leading predictive analytics initiatives using traditional ML techniques including regression, classification, clustering, and time series forecasting • Hands-on experience with time series forecasting models including SARIMA, Prophet, and other ML-based forecasting approaches • Proficiency in Python with scikit-learn, XGBoost, Pandas, and NumPy • Knowledge of supervised and unsupervised machine learning techniques, including clustering, decision tree learning, and artificial neural networks • Ability to translate complex business problems into scalable ML solutions and drive feature engineering strategies and end-to-end model development • Hands-on experience with AWS machine learning services, including SageMaker, training jobs, real-time and batch inference, and processing jobs • Experience leading model deployment on AWS SageMaker with focus on performance optimization, model governance, and measurable business impact • Experience implementing and managing MLOps-based model lifecycles and ML architecture best practices in production environments • Experience with at least one workflow orchestration tool: Airflow, Step Functions, SageMaker Pipelines, or Kubeflow • Ability to create end-to-end solution architecture for model training, deployment, and retraining using native AWS services such as SageMaker and Lambda • Experience building model monitoring and explainability workflows in production environments • Experience defining and driving model governance frameworks and performance monitoring strategies • Ability to collaborate with developers, QA, project managers, and other stakeholders • Experience with Generative AI development • Experience with Infrastructure as Code and CI/CD pipelines

🏖️ Benefits

• Join one of the world’s fastest-growing AI-first digital engineering companies and make a real impact at scale • Lead and collaborate with a high-energy team of talented, driven individuals solving complex, meaningful challenges • Work with Fortune 500 companies and disruptive innovators in a research-driven environment with 60+ patents • Gain hands-on experience with cutting-edge AI, ML, data, and cloud technologies • Continuously upskill • Global and diverse culture built on transparency, diversity, integrity, learning and growth