Data Analyst Lead

Carbon Data Solutions; United States; Remote; USD 90,000 - 130,000; Full time

Job summary

Carbon Data Solutions is seeking an Analytics Platform Lead to guide a Data Science Operations team and advance platforms used to develop, deploy, monitor, and optimize analytics and models.

In collaboration with infrastructure teams, the role focuses on automation, testing, quality control and proactive observability across the Data Science portfolio. Experience in AWS and CI/CD is desirable.

Qualifications

• Proficient in Python, R and SQL with strong data analytics and software skills.
• Experience with shell scripting and version control in a distributed team.
• Familiarity with CI/CD tools (e.g., TeamCity) and observability platforms (Datadog).

Responsibilities

• Lead a data science operations team focused on automation, reliability and quality of service.
• Collaborate with infrastructure teams to advance testing, observability and deployment processes.
• Help manage sprints and product backlog in an Agile environment.

Skills

Python

R

SQL

Shell scripting

CI/CD tooling

Tools

GitHub

TeamCity

Datadog

AWS

Job description

An Analytics Platform Lead is required to lead a team of highly motivated and capable Data Science Operations specialists to advance the platform and processes used to develop, deploy, monitor, track performance and quality, update/maintain Data Science existing and new analytics and data science models. Working with infrastructure platform team, focus is on advancing automation, testing, quality control, observability and proactive of the Data Science portfolio.
Required Technical Skill Set: Python/R/SQL, shell scripting, GitHub (version control), Teamcity or other (CI/CD tools), monitoring tools such as Datadog, awareness of cloud computing environments (AWS).
Required Ability to work as part of a distributed and multidisciplinary team and develop and maintain relationships with internal and external stakeholders.
Required Assist in the management of sprints and product backlog in an Agile environment.
Required Focus of team is automation, reliability and quality of service for Data Science products.
Desirable Application of advanced analytics, machine learning, artificial intelligence, and/or optimization algorithms. Understanding of data science fundamentals, methods and techniques.
Desirable Comfortable with analytics and data science project life cycle: scoping, building, testing, implementation, maintenance, tracking and quality assessment of analytics and models.

Originally posted on Himalayas