Machine Learning Analyst

TextUs is an award-winning provider of SMS cloud communications with managed CRM and ATS integrations. Instead of waiting days for an email response, our real-time communication combines conversational text messaging, cloud-voice service and personalized automation to help our customers connect with people in real time and build better relationships.

OVERVIEW

The data team at TextUs is helping the business solve challenging problems by discovering actionable insights in the universe of data we have across the company. We want to leverage state of the art data science tools and techniques to help foster an environment of data-based decision making. This work has the potential to unlock serious growth opportunities across the business and will be impactful from business operations to product development. This group is responsible for developing the algorithms, building and optimizing models, and productionizing the necessary data pipelines to power our ML and AI initiatives.  

WHAT YOU'LL DO

• Data Engineering & Pipeline Support:
  • Assist in designing and developing data pipelines from various internal and external sources.
  • Help build, cleanse, and audit data pipelines to ensure high-quality outputs.
  • Collaborate with engineers and data scientists to implement robust data infrastructure.
  • Contribute to automating workflows and data processes.
• Machine Learning & Data Science:
  • Support the building and deployment of machine learning models.
  • Participate in data processing, feature selection, model training, testing, deployment, and monitoring under the guidance of senior team members.
  • Use machine learning and NLP technologies to enhance engagement and optimize messaging.
  • Stay updated with AI/ML advancements and share insights with the team.
  • Learn and apply emerging technologies with mentorship from experienced colleagues.
• Collaboration & Knowledge Sharing:
  • Work with Product, Engineering, and Business teams to align on product features and integrate ML capabilities.
  • Learn from and support senior team members in training others on using data and machine learning insights.
  • Participate in cross-functional processes to incorporate data science into product development.
• Product & Business Insights:
  • Assist in developing user metrics and benchmarks to improve engagement and best practices.
  • Help identify key KPIs and design experiments to validate product developments and business outcomes.
  • Contribute to building and maintaining analytics dashboards to deliver actionable insights.
• Growth & Learning:
  • Eagerly learn from experienced colleagues and actively …