Sr. Data Scientist, Capacity Planning

Amazon Web Services (AWS)

Dallas (TX)

Vor Ort

USD 159.000 - 215.000

Vollzeit

14 Tage+
Bewerbungsgenerator

Verschicke keinen Standard-Lebenslauf — erstelle einen Lebenslauf und ein Anschreiben, die genau auf diese Rolle zugeschnitten sind.

Schaffe es an den ATS-Filtern vorbei

Zusammenfassung

Amazon Web Services, Inc. in Dallas, TX is seeking a data scientist to build forecasting, optimization, and predictive models that improve support operations and cost efficiency.

You will partner with data engineering, product, and finance teams to drive data-driven decisions across the network. The ideal candidate has 5+ years of data querying and Python/R experience, strong modeling skills including multinomial logistic regression, and experience with visualization tools.

Qualifikationen

  • 5+ years of experience with data querying languages (e.g., SQL) and scripting languages (e.g., Python) or statistical software (e.g., R, SAS, Matlab).
  • 4+ years of data science experience.
  • Experience with statistical models such as multinomial logistic regression.

Aufgaben

  • Establish data management and strategy frameworks for data collection, storage and quality.
  • Collaborate with cross-functional teams to identify data challenges and develop data-driven solutions.
  • Conduct research to understand data needs and assess infrastructure gaps.
  • Leverage large-scale data processing frameworks (e.g., Spark, Hadoop) for model training.
  • Evaluate and improve machine learning models based on real-world feedback.
  • Develop ML models that drive business value and forecast outcomes.
  • Analyze data domains (customer, market, financial, operations) to inform strategy.
  • Identify bottlenecks and opportunities to reduce costs and improve customer outcomes.

Kenntnisse

SQL
Python
R
SAS
Matlab
Multinomial logistic regression

Tools

AWS QuickSight
Tableau
R Shiny

Jobbeschreibung

Description

Do you have proven analytical capabilities to identify business opportunities, develop predictive models and optimization algorithms to help us build state of the art Support organization?

Background

At Amazon, we are working to be the most customer-centric company on earth. To get there, we need exceptionally talented, bright, and driven people. We set big goals and are looking for people who can help us reach and exceed them. Amazon Web Services (AWS) is one of the world’s most comprehensive and broadly adopted cloud platform, offering over 200 fully featured services from data centers globally. Amazon Web Services, Inc. provides services for broad range of applications including compute, storage, databases, networking, analytics, machine learning, and artificial intelligence (AI), Internet of Things (IoT), security, and application development, deployment, and management.

AWS Support's Capacity Planning team is looking for a strong, talented Data Scientist to model contact and volume forecasting, discovering insights and identifying opportunities through the use of statistics, machine learning, and combinatorial optimization problems to drive business and operational improvements. You are passionate about building solutions that will help drive a more efficient operations network and optimize cost. In this role, you will partner with data engineering, tooling team, operations, training, workforce management and finance teams, driving optimization and prediction solutions across the network influencing the long-term strategy of the business.

We are looking for an experienced and motivated Data Scientist with proven abilities to build and manage modeling projects, forecasting solutions, identify data requirements, build methodology and tools that are statistically grounded. You are an expert in the areas of data science, forecasting, optimization, machine learning and statistics, and is comfortable facilitating ideation and working from concept through execution. You are customer obsessed, innovative, independent, results-oriented and enjoys working in a fast-paced growing organization. An interest in operations, process improvement is helpful. The ability to embrace this ambiguity and work with a highly distributed team of experts is critical. While this is a small team, there is opportunity to own globally impactful work and grow your career in technical, programmatic or people leadership. You will likely to work in Python or R, building forecasting, predictive and optimization models. Your problem solving ability, knowledge of data models and ability to drive results through ambiguity are more important to us.

Key job responsibilities
  • Establish and execute data management and strategy frameworks including data collection, storage, integration and ensuring data quality and integrity
  • Collaborate with cross-functional teams to identify data-related challenges and opportunities, develop data-driven solutions, and align data strategy with the organization's overall objectives
  • Conduct thorough research and analysis to understand organization's data needs and requirements, including evaluating existing data infrastructure and systems, identifying gaps and areas for improvement, and proposing innovative solutions.
  • Leverage large-scale data processing frameworks, such as Apache Spark or Hadoop, to handle big data and ensure efficient model training and evaluation
  • Continuously evaluate and improve machine learning models by incorporating feedback from stakeholders, monitoring their performance in real-world scenarios, and exploring new algorithms and techniques to enhance accuracy and efficiency
  • Develop and implement machine learning models that drive business value:
  • Analyze historical data and identifying patterns, to forecast future outcomes and provide inputs into strategic plans
  • Analyze customer data and market trends, to help develop targeted go to market strategies that our efforts are data driven and have a higher chance of success
  • Analyze financial data, to identify cost-saving opportunities, optimize pricing strategies, and forecast revenue growth helping the leaders to make informed decisions
  • Analyze operational data, to identify bottlenecks, inefficiencies, and areas for process improvement, helping in streamlining operations, reducing costs, and improving customer satisfaction
About The Team

About Us

Diverse Experiences

AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.

Why AWS?

Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.

Inclusive Team Culture

Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon conferences, inspire us to never stop embracing our uniqueness.

Mentorship & Career Growth

We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

Work/Life Balance

We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.

Basic Qualifications
  • 5+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
  • 4+ years of data scientist experience
  • Experience with statistical models e.g. multinomial logistic regression
Preferred Qualifications
  • 2+ years of data visualization using AWS QuickSight, Tableau, R Shiny, etc. experience
  • Experience managing data pipelines
  • Experience as a leader and mentor on a data science team

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.

USA, TX, Dallas - 159,200.00 - 215,300.00 USD annually

USA, WA, Seattle - 159,200.00 - 215,300.00 USD annually

Company

Amazon Web Services, Inc.

Job ID: A10477487

Hol dir deinen kostenlosen, vertraulichen Lebenslauf-Check.

oder ziehe deine Datei hierhin.

Similar jobs

Ähnliche Jobs, die dir auch gefallen könnten

Data Scientist, AWS Support Capacity Planning
Data Scientist, AWS Support Capacity Planning

Amazon Web Services (AWS) • Seattle (WA)

Vor Ort
USD 136.000 - 184.000
RSUs
Sign-on bonus
Health insurance
+2
Sr. Applied Science, Agentic WorkSpaces (AAWS)
Sr. Applied Science, Agentic WorkSpaces (AAWS)

Amazon Web Services (AWS) • Seattle (WA)

Vor Ort
USD 167.000 - 226.000
Health insurance
RSUs
Paid time off
+2
Senior Data Scientist, AWS Central Econ and Science
Senior Data Scientist, AWS Central Econ and Science

Amazon Web Services (AWS) • San Francisco (CA)

Vor Ort
USD 183.000 - 248.000
Health insurance
401(k) matching
Paid time off
+1
Senior Data Scientist, AWS Central Econ and Science
Senior Data Scientist, AWS Central Econ and Science

Amazon Web Services (AWS) • Seattle (WA)

Vor Ort
USD 159.000 - 215.000
Health insurance
401(k) matching
Paid time off
+2
Data Scientist, NA Operations
Data Scientist, NA Operations

Amazon Science • Bellevue (WA)

Vor Ort
USD 108.000 - 160.000
Health insurance
RSUs
401(k) matching
+1
Data Scientist, NA Operations
Data Scientist, NA Operations

Amazon • Bellevue (WA)

Vor Ort
USD 108.000 - 160.000
RSUs
Health insurance
401(k) matching
Data Scientist, NA Operations
Data Scientist, NA Operations

Amazon • Factoria (WA)

Vor Ort
USD 108.000 - 160.000
Health insurance
401(k) matching
Paid time off
+1
Data Scientist, NACP Analytics, NACP Analytics (Fulfillment & Operations)
Data Scientist, NACP Analytics, NACP Analytics (Fulfillment & Operations)

Amazon • Bellevue (WA)

Vor Ort
USD 136.000 - 184.000
RSUs
Health insurance
401(k) matching
+2
Data Scientist, NA Operations
Data Scientist, NA Operations

Amazon • Seattle (WA), Northern (KY)

Vor Ort
USD 108.000 - 160.000
Health insurance
401(k) matching
Paid time off
+1
Sr. Applied Science, Agentic WorkSpaces (AAWS)
Sr. Applied Science, Agentic WorkSpaces (AAWS)

Amazon Science • Seattle (WA)

Vor Ort
USD 167.000 - 226.000