Data Scientist II, Worldwide Design Engineering - Data Science

Amazon Inc.; Asti; Ibrido; EUR 120.000 - 162.000; Tempo pieno

Vantaggi offerti da questo lavoro

RSUs

Comprehensive benefits program

Descrizione del lavoro

Amazon.com Services LLC is seeking a Data Scientist II to analyze fulfillment network trends and drive data-driven decisions for the Worldwide Fulfillment Design and Engineering org. You will own the data science vision and lead ML research strategy, partnering with engineers to deploy scalable AI solutions across the design of the fulfillment network.

You will develop predictive models, design data pipelines, and empower cross-functional teams with actionable insights using SQL, Python, R,

Competenze

• 2+ years of data scientist or similar role involving data extraction, analysis, statistical modeling and communication experience
• 2+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
• Master's degree in a quantitative field, or Bachelor's degree and 5+ years of a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science experience
• Experience developing, deploying and managing AI products at scale

Mansioni

• Analyze, model and interpret data for Amazon warehouse operational performance
• Predictive analysis using Machine Learning models at scale
• Partner with other scientists and engineers to translate frontier AI research into production-grade tools for process design developments
• Data analysis, modeling, network flow prediction using Excel, Pivot tables, VBA, Tableau, SQL (Amazon Redshift), R, Python
• Innovate and simplify data solutions to standardize and enable automation
• Support Worldwide Engineering teams by providing necessary data for of process flows and selection of various MHE's
• Support process improvement initiatives among site operations, engineering, and corporate systems groups by managing data pipelines
• Develop data and optimization-based solutions to the best-in-class process flow to improve the throughput of the fulfillment facilities

Conoscenze

Data analysis

SQL

Python

R

Tableau

Excel

Pivot tables

VBA

Formazione

Master's degree in a quantitative field

Bachelor's degree + 5+ years of quantitative field experience

Strumenti

SQL (Redshift)

Tableau

Excel

R

Python

VBA

Descrizione del lavoro

Data Scientist II, Worldwide Design Engineering - Data Science

Job ID: 10521209 | Amazon.com Services LLC

Are you a data enthusiast? Are you a creative big thinker who is passionate about using data and optimization tools to direct decision making and solve complex and large-scale challenges? If so, then this position is for you! We are looking for a motivated individual with strong analytic and communication skills to join the effort in evolving the fulfillment center network of tomorrow.

At Amazon Worldwide Fulfillment Design and Engineering, we are designing the future and if you are in quest of an iterative fast-paced environment, where you can drive innovation through data visualization products, advance analytics and machine learning at scale, this is your opportunity.

In this role, your main focus will be to analyze fulfillment network trends, identify business opportunities, provide project direction, and communicate design and technical requirements within the team and across stakeholder groups. You will own the science vision, lead AI/ML research strategy and roadmap for the org, drive metrics, assist science groups in initial solution design and audit new flow implementations. A successful candidate in this position will have a background in communicating across significant differences, prioritizing competing requests, and quantifying decisions made.

Key job responsibilities

• Analyze, model and interpret data for Amazon warehouse operational performance.
• Predictive analysis using Machine Learning models at scale.
• Partner with other scientists and engineers to translate frontier AI research into production-grade tools for process design developments.
• Data analysis, modeling, network flow prediction using Excel, Pivot tables, VBA, Tableau, SQL (Amazon Redshift), R, Python.
• Innovate and simplify data solutions to standardize and enable automation.
• Support Worldwide Engineering teams by providing necessary data for of process flows and selection of various MHE's.
• Support process improvement initiatives among site operations, engineering, and corporate systems groups by managing data pipelines.
• Develop data and optimization-based solutions to the best-in-class process flow to improve the throughput of the fulfillment facilities.

A day in the life

Amazon offers a full range of benefits for you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include:

1. Medical, Dental, and Vision Coverage
2. Maternity and Parental Leave Options
3. Paid Time Off (PTO)
4. 401(k) Plan

If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply!

Basic Qualifications

• 2+ years of data scientist or similar role involving data extraction, analysis, statistical modeling and communication experience
• 2+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
• Master's degree in a quantitative field, or Bachelor's degree and 5+ years of a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science experience
• Experience developing, deploying and managing AI products at scale

Preferred Qualifications

• Experience with machine learning/statistical modeling data analysis tools and techniques, and parameters that affect its performance
• Knowledge of relevant statistical measures such as confidence intervals, significance of error measurements, development and evaluation data sets, etc.
• Knowledge of diverse MHS, industrial mechanical and electrical systems and automation, controls and robotics systems

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, WA, Bellevue - 136,000.00 - 184,000.00 USD annually

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Veterans, military spouses, and people with disabilities are encouraged to apply.