Compensation Overview

Job Description

At LinkedIn, we trust each other to do our best work where it works best for us and our teams. This role offers a hybrid work option, meaning you can both work from home and commute to a LinkedIn office, depending on what’s best for you and when it is important for your team to be together

Data and Business Intelligence Staff Solution Architect

The Central Operations organization is responsible for building the ultimate go-to-market engine to connect our solutions with customer needs at scale. As a Data & BI Staff Solution Architect, you will be partnering with senior leaders to crack the most important strategic topics to drive operational excellence and ultimately increase customer value. This role is responsible for leading data-driven recommendations, designing, building and deploying AI models for classification, clustering and prediction, integrating AI solutions, converting data into business insights using data processing and data mining techniques, and scaling operational and planning processes in partnership with cross-functional stakeholders. 

The ideal candidate should have a strategic mindset and strong communications skills to collaborate with cross-functional stakeholders and drive critical business decisions. The candidate should also be able to handle highly sensitive, confidential, and non-routine information, have high attention to detail, be open-minded to challenge the status quo and work in a rapidly changing organization in close collaboration with business partners. 

Responsibilities: 

• Lead data-driven recommendations and insights to support strategic projects across Central Operations 
• Lead cross-functional teams in specific initiatives; recognizes dependencies between teams; drive and clarify ownership of those dependencies.   
• Understand the business, track operational performance, provide insights and recommendations.  
  • Independently manage expectations from stakeholders; manages deadlines/timeframes for larger initiatives and projects with minimal guidance on prioritization or dependencies. 
• Deploy the models in production systems & monitor/troubleshoot/debug production issues related to models. 
• Design, develop, test and deploy ML models. 
• Collaborate closely with partner teams in infrastructure and AI to integrate with other systems to run a seamless ML pipeline. 
• Translate unstructured, complex business problems. 

Qualifications

Basic Qualifications: 

• BS in Computer Science or related technical discipline
• Experience with machine learning, personalization algorithms, privacy enhancing technologies (PETs), optimization algorithms, and/or deep-learning techniques
• 7+ years of experience in Python, R or Scala. And SQL
• Experience with building AI models. 
• Background in analytical and technical skills, with clear attention to detail 
• Experience with deploying AI models (On-Premises/Cloud) 
• Experience with big data processing. Experience with Hadoop or other MapReduce paradigms, and associated languages such as Pig, Hive, etc.
• Knowledge in ETL process using Databricks – PySpark.
• Experience in deploying machine learning models in Azure cloud
   

Preferred Qualifications: 

• Ability to select the right statistical methods for a given data science problem. 
• Strong fundamentals in Statistics and Optimization 
• Experience with solution building and architecting with public cloud offerings such as Amazon Web Services, DynamoDB, ElasticSearch, S3, Databricks, Spark/Spark-Streaming, GraphDatabases.
• Experience with distributed data systems such as Hadoop and related technologies (Spark, Presto, Pig, Hive, etc.) 
• MS or PhD in Computer Science or related technical discipline
• Track record of producing papers in conferences such as KDD, ... and Patenting Innovation.
• Background in any one of programming language (C#, Java, PHP, JavaScript) 
• Understanding and experience building RESTful APIs and microservices
• Created and migrated the codes between environments using Azure Dev-Ops CI/CD framework
• Experience in integrating AI solutions with different systems and software. 
• Exposure to Deep Learning and Reinforcement Learning is a plus. 

Suggested Skills:

• Python
• SQL
• Machine Learning

LinkedIn is committed to fair and equitable compensation practices.

The pay range for this role is $119,000 - $193,000. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to skill set, depth of experience, certifications, and specific work location. This may be different in other locations due to differences in the cost of labor.

The total compensation package for this position may also include annual performance bonus, stock, benefits and/or other applicable incentive compensation plans. For more information, visit https://careers.linkedin.com/benefits.