Data Scientist Intern

Hi, were Carbyne. Were on a mission to help emergency call centers save lives every day. As the leader in emergency collaboration technologies, were building a platform that brings game-changing capabilities to people in crisis, such as live video, instant chat, and location tracking. Our platform unifies the flow of life-saving information to emergency call centers, so they can handle emergencies faster than ever, and get to the right people, in the right place, at the right time. We currently provide services to over 400 million people in over eight countries around the world, and partner with Google, Cisco, Amazon, and Microsoft to deliver life-saving technologies. Want to join our mission-driven team? Read on.

About the role

Were seeking a Winter 2021 Data Science Intern to join our team. Your role will be to analyze data, interpret results, training models, and expand Carbynes algorithmic product features.

To be successful in this role, you will work with our global R&D Team on our high-priority, internal Business Intelligence projects, and initiatives. You will be actively involved in driving the delivery of specific projects.

You will experience what defines our culture while honing the skills which separate our development teams from others. Working to support internal and external customer needs, you will collaborate with multi-functional teams, receive mentorship, and gain insight into our values-driven process. Our goal is both to support your growth and development while empowering you for a successful start to your career.

Heres what youll be working on:

• Design and build data and ML pipelines, data visualizations/dashboards, and prepare data for ML
• Bring a project from requirements gathering through to delivery of the technical solutions based on business requirements while meeting quality, security, and accuracy
• Evaluate and learn about new cloud technologies to provide a competitive market perspective
• Help develop and implement user-training programs for service products and projects
• Verify functionality and quality of projects before release to ensure acceptance criteria are met

Requirements

• Must have strong analytical, project management & presentation skills.
• Foundational understanding or experience applying statistical concepts to real-world problems (A/B testing, logistic regressions, etc.).
• Knowledge of SQL and experience working with Big Data
• Experience with data science and machine learning (Python) preferred
• Knowledge of data visualization tools such as Power BI or Tableau
• Familiarity with statistical analysis correlation, regression, etc.
• Background in applied statistics or machine learning
• Strong communications skills (written and verbal) and interpersonal skills
• You will be working towards a BSc degree or Masters equivalent in Data Science, Information Systems, or another relevant field; Graduating in December 2022 or later.
• Thrive in an ever-changing and quickly growing work environment.

Bonus points for:

• Experience in predictive modeling, data science, and analysis
• Experience giving data presentations with graphical or data visualization tools Preferred qualifications Comfortable in a Linux environment Experience with Amazon Web Services (AWS), e.g. Redshift

What else were looking for:

Were a mission-driven team with a strong set of values. We take them pretty seriously here at Carbyne, and want to make sure that anyone who joins our team takes them seriously, too. If you grabbed coffee with any of our team members, you would see that we:

• Innovate. We think differently, and dont lean on standard conventions.
• Strive to be better. Were always looking to improve. We define goals and measure ourselves against them regularly.
• Take ownership. We own our actions, complete our missions, and hold ourselves accountable for both. We care deeply about the success of Carbyne, our customers, our partners, and each other.
• Are customer-first. We focus on making sure our customers are successful, and we build trust and practice full transparency at all times.