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Help us challenge assumptions, uncover bias, and remove barriers—because progress starts with fresh ideas. You’ll find belonging, purpose, and a team that welcomes you—because when you feel valued, you’re empowered to do your best work.

Job Summary

The Senior Data Scientist designs and deploys statistical, forecasting, and machine learning solutions to solve complex business problems. This role works with cross-functional teams to build production-ready models, generate actionable insights, and improve planning and decision-making at scale.

The role requires strong expertise in statistics, time series analysis, probabilistic forecasting, machine learning, and Google Cloud Platform (GCP).

 

Responsibilities

Statistical Modeling & Forecasting

• Build and deploy statistical and probabilistic forecasting models for demand, capacity, and trend analysis

• Apply time series methods including regression-based models, ARIMA/SARIMA, and state-space models

• Define modeling assumptions, forecast uncertainty, and evaluation methods

Machine Learning & Predictive Modeling

• Build and deploy machine learning models for forecasting and prediction, including regression, tree-based models, gradient boosting and neural networks

• Select statistical or ML approaches based on accuracy, interpretability, robustness, and operational needs

• Develop features and run experiments to improve model performance

MLOps & Production Deployment

• Own the model lifecycle, including development, backtesting, deployment, monitoring, and retraining

• Implement model monitoring, performance tracking, and data drift detection

• Ensure models are versioned, reproducible, and production-ready

Data Engineering & Modeling

• Perform exploratory data analysis, feature engineering, and hypothesis testing on large, complex datasets 

• Identify data requirements for forecasting and predictive modeling, including key inputs, data gaps, and quality needs 

• Work with big data technologies and distributed data processing to support scalable modeling 

• Partner with data engineering teams to ensure data quality, availability, and efficient data pipelines

Visualization & Insights

• Create visualizations to communicate forecasts, trends, and model outputs

• Translate model results into actionable insights for business and operational stakeholders

Collaboration & Stakeholder Engagement

• Work closely with product managers, engineers, and business teams to define forecasting and analytics requirements

• Communicate modeling approaches, assumptions, and results clearly to technical and non-technical stakeholders

Qualifications

• 7+ years of experience in data science, applied statistics, or machine learning

• Strong foundation in statistics and experience applying statistical methods in production

• Proven experience with time series analysis and probabilistic forecasting

• Hands-on experience with machine learning models such as regression, boosting, and neural networks

• Experience owning production data science models, including deployment and monitoring

• Experience working with large datasets and using SQL and Python for analytical and modeling workflows

• Proficiency in Python and common DS/ML libraries (e.g., pandas, NumPy, scikit-learn, statsmodels, PyTorch/TensorFlow)

• Experience working on Google Cloud Platform (GCP)

• Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, Data Science, or a related quantitative field

Equinix is committed to ensuring that our employment process is open to all individuals, including those with a disability.  If you are a qualified candidate and need assistance or an accommodation, please let us know by completing this form.

Equinix is an Equal Employment Opportunity and, in the U.S., an Affirmative Action employer.  All qualified applicants will receive consideration for employment without regard to unlawful consideration of race, color, religion, creed, national or ethnic origin, ancestry, place of birth, citizenship, sex, pregnancy / childbirth or related medical conditions, sexual orientation, gender identity or expression, marital or domestic partnership status, age, veteran or military status, physical or mental disability, medical condition, genetic information, political / organizational affiliation, status as a victim or family member of a victim of crime or abuse, or any other status protected by applicable law. 

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