Data Scientist / AI Engineer

What we can offer: 

A crafted employee experience designed to foster professional growth, a focus on health & well-being and an internal community that will set you up for success. 

We offer an environment that enables colleagues to demonstrate their capabilities, focus on their work and create value.  At LG, you're encouraged to take a creative and individual approach to challenges with strong emphasis placed on performance and skill—and equal, merit-based opportunities across the board.  We want our colleagues to grow with our global business.  That's why we deliver sure rewards for exceptional performance and offer industry-leading benefits.  Come join the team! 

 The Opportunity:

We are looking for a highly versatile Data Scientist / AI Engineer who can work at the intersection of data science, AI engineering, internal product, operations, and business stakeholders. This role is ideal for someone who can analyze large-scale operational data, identify opportunities for automation and optimization, and build practical AI-powered tools that improve Contact Center and Voice of Customer operations.

The ideal candidate is not only strong in analytics and machine learning, but also comfortable building lightweight applications, integrating AI APIs, creating dashboards, presenting ideas to stakeholders, and working closely with cross-functional teams to turn ambiguous business problems into scalable solutions.

This person will support contact center operations by delivering actionable insights, automating manual workflows, improving operational efficiency, and contributing to reusable AI frameworks that can be scaled across teams and use cases.

A key focus of this role is to leverage AI and contact center call data to identify agent performance gaps, customer pain points, process issues, and quality risks, and translate those findings into practical corrective actions and coaching recommendations for agents and supervisors. The candidate will be expected to go beyond reporting and insight generation by helping operational teams take measurable actions that improve agent behavior, call quality, customer experience, and overall contact center performance.

Responsibilities:

• Analyze contact center, customer, operational, and Voice of Customer data to identify trends, monitor KPIs, and provide actionable insights.
• Build and automate dashboards, reports, and analytics workflows using Python, SQL, BigQuery, Looker, and related tools.
• Develop AI, automation, and optimization solutions to improve contact center performance, agent productivity, quality monitoring, and customer experience.
• Build internal tools and prototypes using Python, FastAPI, APIs, and front-end technologies as needed.
• Analyze call transcripts, QA data, CRM notes, and customer feedback to identify process gaps, coaching opportunities, and improvement areas.
• Partner with business and technical stakeholders to define requirements, validate solutions, and drive adoption.
• Prepare presentations, business cases, and executive updates for analytics, AI, and automation initiatives.

Education / Experience (Requirements):

• Bachelor’s degree in Data Science, Computer Science, Statistics, Engineering, Mathematics, or a related quantitative field.
• Strong experience with Python, SQL, data analysis, automation, and dashboard/report development.
• Experience with BI tools such as Looker, Tableau, Power BI, or similar platforms.
• Knowledge of machine learning, AI APIs, LLMs, prompt engineering, or generative AI tools.
• Ability to build internal tools or prototypes using FastAPI, Flask, JavaScript, HTML/CSS, or similar technologies.
• Strong analytical, communication, and presentation skills with the ability to translate data into business recommendations.
• Ability to manage multiple priorities and work independently in a fast-paced environment.

Preferred Qualifications:

• Experience with contact center, customer service, CRM, telephony, QA, chatbot/IVR, or Voice of Customer data.
• Familiarity with contact center KPIs such as AHT, SLA, FCR, CSAT, NPS, backlog, and agent utilization.
• Experience with cloud platforms, AI agents, RAG, internal copilots, workflow automation, MLOps, Git, Docker, or CI/CD.
• Experience with forecasting, optimization, workforce planning, or process improvement.

Technical Skills

• Python, SQL, BigQuery, Looker, Excel, Java, FastAPI, Flask, REST APIs, HTML/CSS, JavaScript, LLMs, GPT APIs, NLP, machine learning, GCP/AWS, Git, Docker.

#LI-TF1