Analytics Engineer: Data Pipelines & ML for Insights

LEX Innovations; Shelton (CT); On-site; USD 95,000 - 140,000; Full time

Job summary

LEX Innovations in Shelton, CT is seeking an Analytics Engineer to design and maintain data pipelines, models, and analytics tools that drive business decisions.

The role focuses on applying data science techniques to build predictive models and optimize manufacturing, product development, and sales strategies, collaborating with cross-functional teams to deliver insights and analytics solutions.

Qualifications

• 2+ years in data engineering, data science, or related role, preferably in manufacturing.
• Proficiency in SQL, Python for data manipulation and ML tasks.
• Experience with ETL, data warehousing, cloud platforms, and BI tools.
• Familiarity with big data frameworks (Hadoop/Spark) is a plus.
• Strong communication and collaboration skills to translate technical concepts.

Responsibilities

• Design, build, and maintain scalable data pipelines from multiple sources.
• Ensure data is clean, reliable, and ready for analysis and data science.
• Optimize data workflows for performance and cost.
• Develop data models reflecting business processes and KPIs.
• Create predictive models and ML algorithms to enhance decision-making.
• Collaborate with engineers, product teams, and stakeholders to integrate data science into products.
• Provide training and support on data tools and analytics best practices.
• Stay current with data engineering and analytics technologies.

Skills

SQL

Python

Data Modeling

Data Science

Statistics

Cross-functional collaboration

Education

Bachelor's degree (Business Analytics, CS, Data Eng, Data Science)

Tools

ETL tools

Data Warehousing

AWS

Azure

Google Cloud

Power BI/Tableau/Grafana

Hadoop

Spark

TensorFlow

scikit-learn

Job description

LEX Innovations in Shelton, CT is seeking an Analytics Engineer to design and maintain data pipelines, models, and analytics tools that drive business decisions.

The role focuses on applying data science techniques to build predictive models and optimize manufacturing, product development, and sales strategies, collaborating with cross-functional teams to deliver insights and analytics solutions.