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Job description
You have MS or PhD in Mathematics, Computer Science, Engineering, or Economics (required).
You are an expert in building and deploying recommender systems at scale to enhance customer journey experiences on websites and apps.
You are adept in designing and implementing machine learning solutions to enhance site search.
You have 3-6 years of experience in Big Data environment specifically Hive/Spark where you have deployed reliable models that scale smoothly on high-volume (1TB+) & high-dimensionality (500+ variables per schema) data.
You have worked with massive structured/unstructured data sets before and have a strong grip on machine learning techniques especially able to debug an algorithm with ease.
Given a data problem you know the right data science technique to be applied (such as GLM Regression (linear, logit, multinomial), kMeans/Hierarchical Clustering, Principle Component Analysis, Decision Tree (RF, GBM, XGboost, Neural Networks, Bayesian Statistics, Times Series, & A Priori, etc.) & Deep Learning based recommendations, Market-Based analysis, Collaborative filtering, Content filtering, etc.
You are a solid coder who uses SQL & (Python/Spark/R) to deploy machine learning products into production.
You are highly enthusiastic about uncovering actionable insights from data and conveying these insights to businesses as stories that stick.
You are a strong analytical person who loves solving business problems using massive data sets.
You interface with leadership and team members to get clarity on your requirements, end goals, and deliverables.
You are detail-oriented but never lose sight of deadlines.
You always have an eye on the products you deploy and never assume that everything is ok.
You are comfortable following the procedures and coding standards set by the organization
Role and Responsibilities
Role And Responsibilities: Must Have Soft Skills –
Proactive and sometimes Reactive
Think and Jump right in attitude
Need to be an independent contributor simultaneously valuing feedback from team members
Work Style –
Be analytical and solve problems without losing sight of end goals
Detail-oriented but never lose sight of deadlines
Procedure Oriented
Clearly understand and agree on the standards set by the leadership and how they will be evaluated
Maintain standards most of the time however should voice new procedures and systems
Interpersonal skills-
Need to be able to empathize with the team and be able to control his/her internal state to handle the work load during ambitious targets.
Given ambitious deadlines be proactive and extract clarity on requirements, deliverables, and tasks from PM and leadership
Quality Control –
Constantly check on models and not assume that things are ok.
Core Responsibilities
Follow agile development principles to develop and deploy cutting edge Data Products and POCs using massive sets of structured and unstructured data.
Ensure the data product is deployed with thorough testing and is of the highest quality
Communicate the results to other members of the team in a clear and intuitive manner
Interface with leadership and team members regularly to brainstorm ideas, and communicate progress and risks.
Use JIRA and Confluence as tools for Agile Project planning
Communicate the progress and results in a clear, concise, and timely manner with other stakeholders
Data - Responsibilities
Always looking out for data resources that enhance the model performance
Clearly communicate with PMs about the acquisition of the data sources
Work with team members to develop and design solutions for data products
Write code to clean, munge, analyze, EDA, and visualize terabytes of data
Proficient in EDA and visualizations
Proficient in building, testing, and deploying scalable and reliable machine-learning models
Debug the machine learning models with ease
Understand the upstream and downstream interface requirements and design the solutions accordingly
Get proficient in the in-house Data Science tools
Always looking for avenues for automation in data pipelines wherever applicable
Get comfortable in following the Data Science team sprint planning procedures
Clearly communicate with DE about deployment requirements
Work with DE to get the data in Data Lake in required format.
Compliance - Responsibilities
Ensure completeness of the product
Make sure that the product is of highest quality
Adept in documenting the Modeling work. Ensure that the documentation is complete and reviewed by Sr. Data Scientists.
Ensure code meets team standards
JIRA for agile development
Should have Knowledge and Experience
Experience in Telecom/retail/e-commerce/consumer packaged goods (CPG), Mobile, or Consumer electronics industries
Agile Principles/Scrum/Kanban
Solid understanding of Hadoop (Hive and Impala) & Spark (PySpark/Scala)
Proficient in (Python/Scala/R/Java ) & SQL
Expert in developing and debugging Machine Learning products
Proficient in Data Visualizations
Skills and Qualifications
LI-JL1
Life @ Samsung -
Benefits @ Samsung -
Regular full-time employees (salaried or hourly) have access to benefits including: Medical, Dental, Vision, Life Insurance, 401(k), Employee Purchase Program, Tuition Assistance (after 6 months), Paid Time Off, Student Loan Program (after 6 months), Wellness Incentives, and many more. In addition, regular full-time employees (salaried or hourly) are eligible for MBO bonus compensation, based on company, division, and individual performance.
Necessary Skills and Attributes:
Ability to work cooperatively and build strong relationships with peers and senior leadership locally and globally; sharing ideas and developing effective business processes in support of the company mission. Ability to collaborate and be comfortable dealing with ambiguity, influencing across multiple complex organizations, creating effective business partnerships. Polished interpersonal skills, including strong verbal and written communication skills in local market language. Ability to effectively manage multiple projects, have attention to detail and work effectively under deadlines in a collaborative and matrixed environment.
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Worksite address
mountain view, CA, 94039, US
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.