Data Scientist II, AWS Managed Operations Data Science (MODS)

Amazon; Missouri; On-site; USD 80,000 - 130,000; Full time

Job summary

An innovative opportunity awaits for a Data Scientist II at a leading technology company. This role involves driving data-driven transformation, utilizing advanced analytical techniques to tackle complex business challenges, and collaborating with cross-functional teams. You will lead the end-to-end data science lifecycle, leveraging tools like SQL, Python, and Spark to uncover valuable insights. The position demands a strong foundation in statistical modeling and machine learning, along with a passion for building scalable solutions. If you're ready to make a significant impact in a dynamic environment, this role could be your next career milestone.

Qualifications

• 3+ years of experience as a Data Scientist with strong skills in SQL and Python.
• Master's or Bachelor's degree in a quantitative field with relevant experience.

Responsibilities

• Conduct exploratory data analysis and apply statistical techniques to extract insights.
• Collaborate with teams to understand business requirements and deliver actionable recommendations.

Skills

Data Analysis

Machine Learning

Statistical Modeling

Data Exploration

Problem Solving

Collaboration

Education

Master's Degree in Statistics or related field

Bachelor's Degree in Statistics or related field

Tools

SQL

Python

R

Spark

Hadoop

Job description

Data Scientist II, AWS Managed Operations Data Science (MODS)

Job ID: 2890584 | Amazon Development Center U.S., Inc.

Amazon Web Services (AWS) is the world leader in providing a highly reliable, scalable, low-cost infrastructure platform in the cloud that powers hundreds of thousands of businesses in 190 countries around the world!

Passionate about building, owning and operating massively scalable systems? Want to make a billion-dollar impact? If so, we have an exciting opportunity for you.

The AWS Managed Operations (MO) organization was founded in April 2023, with the objective to reduce operational load and toil through long-term engineering projects. MO is building the best-in-class engineering and operations team that will own the day-to-day operations for AWS Regions; improving the availability, reliability, latency, performance and efficiency to operate AWS regions.

The AWS Managed Operations Data Science (MODS) Team is looking for a Data Scientist to lead the research and thought leadership to drive our data and insight strategy for AWS. You will be expected to serve as a Full Stack Data Scientist. You will be responsible for driving data-driven transformation across the organization. In this role, you will be responsible for the end-to-end data science lifecycle, from data exploration and feature engineering and ETL to model development. You will leverage a diverse set of tools and technologies, including SQL, Python, Spark, Hugging Face and various machine learning frameworks, to tackle complex business problems and uncover valuable insights.

Your product analytics research will provide direction on the technology strategy of the Managed Operations organization. Your Decision Science artifacts will provide insights that inform AWS' Operations and Site Reliability Engineering teams. You will work on ambiguous and complex business and research science problems at scale. You are comfortable working with cross-functional teams and systems.

This position requires that the candidate selected be a U.S. citizen.

Key job responsibilities

1. Collaboration & Cross Functional Relationships: Interact with business and software teams to understand their business requirements and operational processes.
2. Data Exploration and Analysis: Conduct in-depth exploratory data analysis to understand the structure, quality, and patterns within complex datasets. Apply statistical and machine learning techniques to extract insights, identify trends, and uncover hidden relationships in the data.
3. Business Insights and Recommendations: Frame business problems into scalable solutions; translate complex data insights and model outputs into actionable recommendations that address the organization's strategic objectives.
4. Data Pipeline and Infrastructure: Contribute to the design and implementation of data pipelines, data lakes, and other data infrastructure components to support the organization's data-driven initiatives.
5. Metric Development and Monitoring: Define and develop advanced, customized metrics and key performance indicators (KPIs) that capture the nuances of the organization's strategic objectives and operational complexities. Continuously monitor and evaluate the performance of metrics.
6. Prototype models by using high-level modeling languages such as R or in software languages such as Python. A software team will be working with you to transform prototypes into production.
7. Documentation & Continuous Improvement: Create, enhance, and maintain technical documentation.

BASIC QUALIFICATIONS

1. 3+ years of data scientist experience.
2. 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience.
3. 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience.
4. Knowledge of relevant statistical measures such as confidence intervals, significance of error measurements, development and evaluation data sets, etc.
5. Master's Degree in Statistics, Applied Math, Operations Research, Economics, or a related quantitative field with 2+ years' experience in Data Science or related Science discipline, OR, Bachelor's Degree in Statistics, Applied Math, Operations Research, Economics, or a related quantitative field with 5+ years' experience in Data Science or related Science discipline.

PREFERRED QUALIFICATIONS

1. 6+ years of data scientist experience.
2. 4+ years of machine learning, statistical modeling, data mining, and analytics techniques experience.
3. Experience with data scripting languages (e.g., SQL, Python, R, or equivalent) or statistical/mathematical software (e.g., R, SAS, Matlab, or equivalent).
4. Experience with clustered data processing (e.g., Hadoop, Spark, Map-reduce, and Hive).
5. Experience in a ML or data scientist role with a large technology company.

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, 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 this link for more information.

Posted: December 17, 2024 (Updated 1 day ago)