Back to jobs

Senior Analyst, Data Science

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

Develop software programs, algorithms and automated processes that cleanse, integrate and evaluate large data sets from multiple disparate sources

Manipulate large amounts of data across a diverse set of subject areas, collaborating with other data scientists and data engineers to prepare data pipelines for various modeling protocols

  • Build data pipelines and automated processes that cleanse and integrate large data sets

  • Build, validate and maintain AI and machine learning models

  • Develop statistical models and analysis for ad hoc business questions

  • Communicate actionable insights from large data sources to stakeholders

  • Share responsibility for team results, resources, budget and policy adherence

From the employer’s posting
Develop software programs, algorithms and automated processes that cleanse, integrate and evaluate large data sets from multiple disparate sources
Manipulate large amounts of data across a diverse set of subject areas, collaborating with other data scientists and data engineers to prepare data pipelines for various modeling protocols
Build, validate, and maintain AI (Machine Learning (ML) /Deep learning) models
develop statistical models and analysis for ad hoc business focused analysis
Communicate meaningful, actionable insights from large data and metadata sources to stakeholders
Responsible for end results of team and shares responsibility over resources, budget and adherence to policies

What you’ll bring

All qualifications

Core experience

  • Experience with ML and classical predictive techniques such as logistic regression, decision trees, non linear regressions, ANN/CNN, boosted trees, SVM, Tensorflow, visualization packages, and a track record for creating business impact with these methods
  • Ability to work both at a detailed level as well as to summarize findings and extrapolate knowledge to make strong recommendations for change
  • Ability to collaborate with cross functional teams and influence product and analytics roadmap, with a demonstrated proficiency in relationship building
  • Ability to assess relatively complex situations and analyze data to make judgments and recommend solutions
Qualification wording
Experience with ML and classical predictive techniques such as logistic regression, decision trees, non linear regressions, ANN/CNN, boosted trees, SVM, Tensorflow, visualization packages, and a track record for creating business impact with these methods
Ability to work both at a detailed level as well as to summarize findings and extrapolate knowledge to make strong recommendations for change
Ability to collaborate with cross functional teams and influence product and analytics roadmap, with a demonstrated proficiency in relationship building
Ability to assess relatively complex situations and analyze data to make judgments and recommend solutions
Apply at Gapinc

Posting record

Report an error

Open 5 monthsWe first saw this posting 178 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.

Status in our records
Live
First seen by us
May 10, 2026178 days ago
Recorded sightings
99
Last seen by us
Nov 4, 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 178

Up longer than most. Similar jobs usually come down between day 7 and day 55.

From 9,988 similar postings that came down. Coming down is not always a hire.

Gapinc is hiring

10 open jobs

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

  • Hiring at a steady pace
  • Takes jobs down at a usual pace
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
  • R
  • SQL
  • Azure
  • Hive
  • Spark
  • TensorFlow
Where the posting names them
Who You Are - Advanced proficiency in R, Python, Spark, Hive (or other MR), and common scripting languages for E2E pipeline Advanced proficiency using SQL for efficient manipulation of large datasets in on prem and cloud distributed computing environments, such as Azure environments - Experience with ML and classical predictive techniques such as logistic regression, decision trees, non linear regressions, ANN/CNN, boosted trees, SVM, Tensorflow, visualization packages, and a track record for creating business impact with these methods
- Advanced proficiency in R, Python, Spark, Hive (or other MR), and common scripting languages for E2E pipeline Advanced proficiency using SQL for efficient manipulation of large datasets in on prem and cloud distributed computing environments, such as Azure environments - Experience with ML and classical predictive techniques such as logistic regression, decision trees, non linear regressions, ANN/CNN, boosted trees, SVM, Tensorflow, visualization packages, and a track record for creating business impact with these methods - Ability to work both at a detailed level as well as to summarize findings and extrapolate knowledge to make strong recommendations for change

Your next step

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

Applying through Workday

  • You create an account with each employer before you can upload anything. Every Workday employer has its own account, so one sign-up doesn’t carry over.
  • “Autofill with Resume” comes right after sign-in, before the My Information and My Experience steps. Check every field it fills in those steps, since that’s what recruiters see.
  • Your application status lives in that employer’s Candidate Home, under the same sign-in.

Already applied? Track this application

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 ↗

About the Role

The Customer Analytics Team at Gap Inc. applies data analysis and machine learning techniques to drive business benefits for Gap Inc. and its brands.  The team’s focus is on creating analytical capabilities to support customer acquisition and retention, personalization and marketing at Gap Inc. Areas of expertise include segmentation, targeting, forecasting, marketing effectiveness measurement and optimizations, customer behaviors, site analytics and business growth initiatives. You will support the team to build and deploy Data and Analytics capabilities, in partnership with GapTech, PDM, Central Marketing & business partners across our brands.

What You'll Do

  • Develop software programs, algorithms and automated processes that cleanse, integrate and evaluate large data sets from multiple disparate sources

  • Manipulate large amounts of data across a diverse set of subject areas, collaborating with other data scientists and data engineers to prepare data pipelines for various modeling protocols

  • Build, validate, and maintain AI (Machine Learning (ML) /Deep learning) models, diagnose and optimize performance and develop statistical models and analysis for ad hoc business focused analysis

  • Communicate meaningful, actionable insights from large data and metadata sources to stakeholders

  • Responsible for quality of services and advice in meeting business partner needs

  • Responsible for end results of team and shares responsibility over resources, budget and adherence to policies

Who You Are

  • Advanced proficiency in R, Python, Spark, Hive (or other MR), and common scripting languages for E2E pipeline Advanced proficiency using SQL for efficient manipulation of large datasets in on prem and cloud distributed computing environments, such as Azure environments

  • Experience with ML and classical predictive techniques such as logistic regression, decision trees, non linear regressions, ANN/CNN, boosted trees, SVM, Tensorflow, visualization packages, and a track record for creating business impact with these methods

  • Ability to work both at a detailed level as well as to summarize findings and extrapolate knowledge to make strong recommendations for change

  • Ability to collaborate with cross functional teams and influence product and analytics roadmap, with a demonstrated proficiency in relationship building

  • Ability to assess relatively complex situations and analyze data to make judgments and recommend solutions

Source details

View original posting ↗

Source notes

Source excerpts

Selected passages from the saved posting. Check the full description for conditions and exceptions.

Pay

No pay amount identified in the saved description.

Location & working pattern

Spoke - Hyderabad

Working pattern and location restrictions need checking in the full posting.

Work authorization

No clear work-authorization passage found. Eligibility is unconfirmed.

Find answers in the posting

AI
How answers work

AI selects complete passages from this posting. Check them for conditions and exceptions.

Uses this posting and your question. No profile needed.