Senior Data Scientist

Key Skills

Deep Learning, Effective communication skills, Machine learning techniques, Mathematical modeling, MATLAB Programming, Python Programming, R Programming, SAS, SQL, Statistical modeling

Job Description

BASIC QUALIFICATIONS

• 5+ years of data scientist or similar role involving data extraction, analysis, statistical modeling and communication experience
• 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
• Master's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science, or Bachelor's degree and 8+ years of professional or military experience
• Experience with FMs and multimodal architectures
• Experience with deep learning and supporting ML solutions
• Experience with design and developing data architecture, data standards and end to end data pipelines

DESCRIPTION

As a Senior Data Scientist with expertise in Machine Learning (ML), development and use of multi-model models, utilizing diverse sets of large data you will work with a team of Applied Scientists and Software Engineers to build innovative foundation models for robotic manipulation utilizing computer vision and scene perception technology. Your role will focus first on feature engineering, data collection and data usage from large data sets across Fulfillment Technologies and Robotics (FTR), with an eye on strategy going forward to unify a data strategy across organizations. This position requires high levels of analytical thinking, ability to quickly approach large ambiguous problems and apply analytics, technical and engineering expertise to rapidly analyze, validate, visualize, prototype and deliver solutions.

Key job responsibilities

• Utilize expertise in feature engineering on massive data sets through exploratory data analysis across existing large data sets in Fulfillment Technologies and Robotics (FTR). Help identify areas where we could create new data sources that would improve training capabilities based on understanding of how different scenes in FCs could impact the trained model and ultimately performance of robotic manipulation.
• Identify data requirements, build methodology and data modeling strategy across the diverse data sets for both short-term and long-term needs
• Work closely with Applied Scientists in building FM solutions, ensuring that the data strategy fits the experimentation paths, as well as contribute to the FM strategy through identifying opportunities based on the data
• Work with and develop large datasets (training/fine tuning) and bring large datasets together to inform both training in FOMO as well as across FTR
• Design and implement data solutions, working closely with engineers to guide on best paths for building data pipelines and infrastructure for model training
• Collaborate across teams both within and outside of FOMO on data strategy

A day in the life

Amazon offers a full range of benefits that support 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:

• Medical, Dental, and Vision Coverage
• Maternity and Parental Leave Options
• Paid Time Off (PTO)
• 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!

We are open to hiring candidates to work out of one of the following locations:

PREFERRED QUALIFICATIONS

• Experience with computer vision and large multi-model models
• Experience with ML with application in robotics
• Experience in building ontologies, taxonomies, and semantic meaning representation frameworks
• Familiarity with database queries and data analysis processes (SQL, R, Matlab, etc.)
• Excellent communication and organizational skills, with a strong attention to detail

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. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $127,300/year in our lowest geographic market up to $247,600/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.