Job description
illingPlatform is an industry-leading, fast-growing SaaS company. Our award-winning, cloud-based revenue lifecycle management platform is leveraged by leading global enterprises to automate and streamline the entire quote-to-cash process. At BillingPlatform, our employees are our most valuable asset, and we believe deeply in a culture of collaboration, accountability, innovation, and transparency. We seek bright, enthusiastic, and creative professionals looking to be part of our incredible team focused on challenging the status quo and driving transformational value to customers.
Backed by leading private equity firms FTV Capital and Columbia Capital, we have achieved remarkable industry recognition for growth, including being listed for the fifth consecutive year on Deloitte’s Technology Fast 500™ list of fastest-growing technology companies and ranked on the Inc 5000 list for four years running.
Our ability to innovate market-leading solutions has been validated by all major industry analyst firms, including being named a Leader in the first-ever Gartner® Magic Quadrant™ for Recurring Billing Applications, and being recognized as the Leader in Forrester Research’s “The Forrester Wave™: SaaS Recurring Billing Solutions.” To learn more about us, visit billingplatform.com.
We are seeking a talented Data Scientist to join our growing team. In this role, you will leverage your expertise in data analysis, AI and machine learning, and cloud computing to tackle challenging problems and unlock the power of data. You will have the opportunity to work on a diverse range of projects, utilizing both GCP and AWS to design, implement, and deploy data-driven solutions. Furthermore, your knowledge of cloud administration and maintenance will be instrumental in ensuring the smooth operation and performance of these critical platforms.
Responsibilities:
Collaborate with cross-functional teams (Engineering, Product, Business) to understand data needs and define project goals.
Design and conduct exploratory data analysis to uncover patterns and trends.
Develop and implement machine learning models utilizing AI and machine learning techniques, as well as GCP and AWS services (e.g., BigQuery, SageMaker, AI Platform).
Clean, transform, and prepare data for analysis using tools and techniques appropriate for cloud platforms.
Evaluate and interpret model results, communicating insights effectively to technical and non-technical audiences.
Stay up-to-date on the latest advancements in AI, machine learning, and cloud technologies.
Demonstrate knowledge of AWS and GCP administration and maintenance, including resource provisioning, security configuration, and performance optimization.
Document work clearly and concisely.
Master’s degree in Data Science, Statistics, Computer Science, or a related field (or equivalent experience).
Strong experience in AI and machine learning techniques, including model development, training, and evaluation.
Proficiency in programming languages such as Python, R, and SQL.
Experience building AI/ML solutions in both GCP and AWS.
Knowledge of AWS and GCP administration and maintenance, including resource provisioning, security configuration, and performance optimization.
Excellent communication and collaboration skills.
Become a part of the team on global initiatives
A high-impact role at a growing SaaS company that values personal growth, accountability, and teamwork
A culture of open collaboration and problem-solving
Ability to work independently and as part of a team
100% remote
Competitive pay
*This role is remote, but we are only considering candidates located in Serbia. This position is not eligible for relocation.
BillingPlatform provides equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, pregnancy, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state or local law.
