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Senior Staff Data Scientist

Pay
Pay not listed
Work setting
Not stated
Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting

What you’ll work on

Full posting
  • Build and deploy statistical and probabilistic forecasting models for demand and capacity

  • Build and deploy machine learning models for forecasting and prediction

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

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

  • Translate model results into actionable insights for business stakeholders

From the employer’s posting
Build and deploy statistical and probabilistic forecasting models for demand, capacity, and trend analysis
Build and deploy machine learning models for forecasting and prediction
Own the model lifecycle, including development, backtesting, deployment, monitoring, and retraining
Perform exploratory data analysis, feature engineering, and hypothesis testing on large, complex datasets
Translate model results into actionable insights for business and operational stakeholders

What you’ll bring

All qualifications

Core experience

  • 5+ years of experience in data science, applied statistics, or machine learning
  • 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)
Qualification wording
5+ years of experience in data science, applied statistics, or machine learning
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)
Education & alternatives
- 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.
Apply at Equinix

Posting record

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Status in our records
Live
First seen by us
Sep 6, 202659 days ago
Recorded sightings
162
Last seen by us
Nov 5, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Time since we first saw it

Day 59

Up longer than most. Similar jobs usually come down between day 7 and day 56.

Well past Equinix’s usual: its jobs come down by about day 26.

From 10,198 similar postings that came down, and 38 of Equinix’s. Coming down is not always a hire.

Equinix is hiring

6 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Hiring at a steady pace
  • Takes jobs down quickly
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • SQL
  • GCP
  • NumPy
  • pandas
  • PyTorch
  • scikit-learn
  • TensorFlow
Where the posting names them
- 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 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)
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
- 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

Your next step

Complete your application on equinix.wd1.myworkdayjobs.com. The employer’s form will show what is required.

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About Equinix

People
About 13,716 in 2025, up 1% from the year before.Annual report (SEC Form 10-K)
Company
Listed as EQIX.
H-1B visas
23 approved for new hires in fiscal 2025.US Citizenship and Immigration Services

Demand for Data Scientist roles

New Data Scientist postings at the employers we follow are down 3% over the last 5 weeks compared with the 5 before.

Weekly new Data Scientist postings at the same employers, from the week of August 17 to the week of October 26. The fewest in a week was 1,411, the most 2,973, and the latest week had 1,826.
August 17Last week

Each bar is one week of new postings. The darkest bars are the last 5 weeks.

Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.

About the role

We file this job under Data Scientist, by the work the posting describes.

Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.

Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.

Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.

US government figures for data scientists

Median yearly pay, May 2025
$120,230
Expected change, 2025 to 2035
34.6% more jobsagainst 3.5% for all jobs

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.

Job description

View original posting ↗

Who are we?

Equinix is the world’s digital infrastructure company®, shortening the path to connectivity to enable the innovations that enrich our work, life and planet. 
 

A place where bold ideas are welcomed, human connection is valued, and everyone has the opportunity to shape their future.

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

  • 5+ 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. 

We use artificial intelligence in our hiring process. Learn more here.


This posting is a new position within our organization.

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Location & working pattern

Bangalore Office BLS2

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Work authorization
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. We use artificial intelligence in our hiring process. Learn more here.

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