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지금 많이 보는 기업

지금 많이 보는 기업

T-Mobile
T-Mobile

German telecommunications company.

Sr Data Scientist- Consumer Analytics

직무데이터 사이언스
경력시니어급
위치Bellevue; Overland Park; Frisco
근무오피스 출근
고용정규직
게시1주 전
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At T-Mobile, we invest in YOU! Our Total Rewards Package ensures that employees get the same big love we give our customers. All team members receive a competitive base salary and compensation package - this is Total Rewards. Employees enjoy multiple wealth-building opportunities through our annual stock grant, employee stock purchase plan, 401(k), and access to free, year-round money coaches. That’s how we’re UNSTOPPABLE for our employees!

Job Overview:

This role leads the application of machine learning techniques and statistical methods to address complex business challenges effectively. It involves collaborating with diverse technical and non-technical stakeholders to deliver data-driven solutions. The role requires expertise across the entire machine learning lifecycle, including problem framing, data collection, model development, deployment, and performance evaluation. Success is measured by the ability to create actionable insights and deploy models that drive informed decision-making and business value. The work impacts organizational outcomes by transforming data into strategic assets that support business objectives and customer needs.

Job Responsibilities:

  • Extract and model large, complex data sets using machine learning, mathematics, statistics, and programming to generate predictive insights

  • Deliver timely, high-quality analysis and actionable recommendations that support intelligent business decision-making

  • Provide senior-level guidance and mentorship by reviewing projects, models, and code to support team development

  • Collaborate with engineering teams to implement and enhance machine learning pipelines and production-ready models

  • Communicate key information and insights to business leaders through verbal, written, and data visualization methods

  • Also responsible for other duties/projects as assigned by business management as needed

Education and Work Experience:

  • Bachelor's Degree plus 5 years of related work experience OR Advanced degree with 3 years of related experience (Required)

  • Acceptable areas of study include Quantitative Discipline (math, statistics, economics, computer science, physics, engineering, etc.) (Required)

  • 4-7 years Industry experience in predictive modeling, data science, and analysis in an ML engineer or data scientist role building and deploying ML models or hands on experience developing deep learning models (Required)

  • 4-7 years Experience with data scripting languages (e.g., SQL, Python, R) (Required)

  • 2-4 years Experience with big data architecture and pipeline, Hadoop, Hive, Spark, Kafka, etc. (Required)

  • 4-7 years Experience articulating and translating business questions and using statistical techniques to arrive at an answer using available data (Required)

  • 4-7 years Experience in data visualization (Required)

  • 4-7 years Experience working with relational database using SQL (Required)

  • 2-4 years Experience in the telecom industry (Preferred)

Knowledge, Skills and Abilities:

  • Mathematics Calculus, linear algebra, statistics, and probability (Required)

  • Programming Expertise in Python and SQL (Required)

  • Machine Learning: Expertise applying machine learning concepts and techniques related to supervised and unsupervised learning (Required)

  • At least 18 years of age

  • Legally authorized to work in the United States

Travel:
Travel Required (Yes/No): No

DOT Regulated:
DOT Regulated Position (Yes/No): No
Safety Sensitive Position (Yes/No): No

Base Pay Range: $106,000 - $191,100

Corporate Bonus Target: 15%

The pay range above is the general base pay range for a successful candidate in the role. The successful candidate’s actual pay will be based on various factors, such as work location, qualifications, and experience, so the actual starting pay will vary within this range.

At T-Mobile, employees in regular, non-temporary roles are eligible for an annual bonus or periodic sales incentive or bonus, based on their role. Most Corporate employees are eligible for a year-end bonus based on company and/or individual performance and which is set at a percentage of the employee’s eligible earnings in the prior year. Certain positions in Customer Care are eligible for monthly bonuses based on individual and/or team performance. To find the pay range for this role based on hiring location, https://paylookup.t-mobile.com/paylookup?reqID=REQ346803¶dox=1

At T-Mobile, our benefits exemplify the spirit of One Team, Together! A big part of how we care for one another is working to ensure our benefits evolve to meet the needs of our team members. Full and part-time employees have access to the same benefits when eligible. We cover all of the bases, offering medical, dental and vision insurance, a flexible spending account, 401(k), employee stock grants, employee stock purchase plan, paid time off and up to 12 paid holidays - which total about 4 weeks for new full-time employees and about 2.5 weeks for new part-time employees annually - paid parental and family leave, family building benefits, back-up care, enhanced family support, childcare subsidy, tuition assistance, college coaching, short- and long-term disability, voluntary AD&D coverage, voluntary accident coverage, voluntary life insurance, voluntary disability insurance, and voluntary long-term care insurance. We don't stop there - eligible employees can also receive mobile service & home internet discounts, pet insurance, and access to commuter and transit programs! To learn about T-Mobile’s amazing benefits, check out www.t-mobilebenefits.com.

Never stop growing!
As part of the T-Mobile team, you know the Un-carrier doesn’t have a corporate ladder–it’s more like a jungle gym of possibilities! We love helping our employees grow in their careers, because it’s that shared drive to aim high that drives our business and our culture forward. By applying for this career opportunity, you’re living our values while investing in your career growth–and we applaud it. You’re unstoppable!

T-Mobile USA, Inc. is an Equal Opportunity Employer. All decisions concerning the employment relationship will be made without regard to age, race, ethnicity, color, religion, creed, sex, sexual orientation, gender identity or expression, national origin, religious affiliation, marital status, citizenship status, veteran status, the presence of any physical or mental disability, or any other status or characteristic protected by federal, state, or local law. Discrimination, retaliation or harassment based upon any of these factors is wholly inconsistent with how we do business and will not be tolerated.

Talent comes in all forms at the Un-carrier. If you are an individual with a disability and need reasonable accommodation at any point in the application or interview process, please let us know by emailing Applicant Accommodation@t-mobile.com or calling 1-844-873-9500. Please note, this contact channel is not a means to apply for or inquire about a position and we are unable to respond to non-accommodation related requests.

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T-Mobile 소개

T-Mobile

T-Mobile

Public

A telecommunications company that provides wireless communication services, including mobile phone and internet services.

10,001+

직원 수

Bellevue

본사 위치

$183B

기업 가치

리뷰

10개 리뷰

3.9

10개 리뷰

워라밸

3.5

보상

4.0

문화

4.2

커리어

3.0

경영진

4.0

72%

지인 추천률

장점

Flexible scheduling and remote work options

Good pay and competitive benefits

Supportive and responsive management

단점

High pressure and demanding work environment

Workload can be overwhelming at times

Limited career advancement opportunities

연봉 정보

7,663개 데이터

Junior/L3

Mid/L4

Senior/L5

Staff/L6

Junior/L3 · Associate Data Scientist

1개 리포트

$117,520

총 연봉

기본급

$90,400

주식

-

보너스

-

$117,520

$117,520

면접 후기

후기 5개

난이도

2.6

/ 5

소요 기간

14-28주

합격률

20%

경험

긍정 20%

보통 80%

부정 0%

면접 과정

1

Application Review

2

Recruiter Screen

3

Phone/Video Interview

4

In-Person Interview

5

Background Check

6

Offer

자주 나오는 질문

Behavioral/STAR

Technical Knowledge

Culture Fit

Past Experience

Customer Service Scenarios