Data Scientist

Public Private Ventures
United States
1 day ago
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Role details

Contract type
Contract
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
3 years minimum
Compensation
$83,200.0 - $93,600.0
Working hours
Regular working hours
Job source

Tech stack

A/B Testing Artificial Intelligence Airflow Amazon Web Services Microsoft Azure Health Informatics Data Visualization DevOps Statistical Hypothesis Testing Python (Programming Language) Machine Learning NumPy
+23 more
Power BI Tensorflow Standard Sql Tableau (Software) Google Cloud Cloud Platform System Feature Engineering Pytorch Prophet Retrieval-Augmented Generation Large Language Models Prompt Engineering Deep Learning Model Validation Pandas Semi-structured Data Git Flow Scikit Learn Information Technology Xgboost Plotly Machine Learning Operations Docker

Job description

Nimara Ventures places senior AI, DevOps and product engineers with US companies. We’re looking for a Data Scientist to turn client data into models and decisions. You’ll work from problem definition through feature engineering, modeling, validation and deployment, and explain results clearly to business stakeholders.

What You’ll Do

  • Frame business problems as data science problems and agree success metrics with stakeholders
  • Clean, explore and engineer features from structured and semi-structured data
  • Build and evaluate predictive models: classification, regression, clustering and time-series forecasting
  • Run experiments and A/B tests, and measure the business impact of models
  • Build anomaly detection and forecasting solutions for operational, financial or industrial data
  • Work with engineers to deploy models and monitor them for drift and performance
  • Create clear dashboards, reports and presentations for non-technical audiences
  • Document methodology, assumptions and results so work can be reproduced

Requirements

  • 3-5 years of hands-on experience in data science or applied machine learning
  • Strong Python (pandas, NumPy, scikit-learn) and SQL
  • Experience with gradient boosting (XGBoost, LightGBM) and model evaluation and validation
  • Experience with time-series forecasting (Prophet, ARIMA or similar)
  • Solid statistics: hypothesis testing, experiment design, probability
  • Experience with at least one cloud platform (AWS, Azure or Google Cloud Platform)
  • Ability to explain technical results to business stakeholders
  • Bachelor’s degree in a quantitative field (Computer Science, Statistics, Engineering, Math or similar)

Preferred

  • Deep learning with PyTorch or TensorFlow
  • NLP or LLM experience (embeddings, RAG, prompt engineering)
  • MLOps tools: MLflow, Docker, Airflow, Git-based workflows
  • Visualization tools: Power BI, Tableau or Plotly
  • Predictive maintenance, financial analytics or healthcare analytics experience
  • Master’s degree in a quantitative field

Work Authorization: Must be legally authorized to work in the US without sponsorship.

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