Description

Pipl is the identity trust company. Our solutions allow organizations to provide frictionless customer experiences and approve more transactions with greater confidence and speed. We use multivariate linking to establish deep connections among more than 330 billion trust signals—email, mobile phone and social media data that spans the globe—and then look at the big picture to derive identity trust

As a Data Scientist, you will collaborate with internal teams and our clients to delve into, grasp, and apply data and insights effectively for trust and fraud applications. You will analyze and utilize Pipl's data through machine learning in order to improve the quality of its trust solutions. You will work closely with other teams including product, MLOps and analytics, to review business problems and identify data requirements necessary to develop predictive models that can help solve them. As a critical part of the team, you are responsible for presenting your findings to stakeholders and clients.

The ideal candidate has a strong background in statistics, machine learning, research design, data analysis, writing production level code, as well as excellent communication and organizational skills. English proficiency is a must. This position is for a “hands-on” type of person that enjoys tackling real-world data challenges with a can-do attitude, mentor mentality, and passion for data.

Responsibilities:

• Architect, develop and deploy data science pipelines. 
• Research and ideate new features, using domain knowledge and statistical methods. 
• Own the process of integrating customer data, analyzing it using our methodology and your data instincts, and make it deliver value to the customer
• Present your findings to stakeholders and external customers. 
• Actively troubleshoot and refine customer models, maintaining a continuous improvement mindset.
• Act as the technical bridge between the customer and the product, making our tools useful, relaying product feedback, and customizing to a client’s needs where necessary
• Work with our clients in a consultative capacity, learning about their particular needs and being their advocate both internally and externally.

Requirements

• A data science professional with at least 2 years of experience and at least a Master’s degree in Computer Science, Statistics, Mathematics, or a related field. Strong preference for additional experience in software, R&D, SaaS, or adjacent fields.
• Very proficient with Python. You have experience with creating production-level code and working knowledge of standard ML packages. You have worked on machine learning pipeline code.
• Proven in your experience in applied machine learning, including familiarity with various forms of regression, classification, supervised and unsupervised learning techniques.
• Skilled in handling, cleaning, analyzing, and presenting data.
• Deep in your understanding of statistics and other mindsets for building models from data; strong data acumen in translating business problems into supervised/unsupervised machine learning problems.
• Proficient in using Git.
• Comfortable with relational database systems and SQL.
• Familiar with cloud technologies (AWS/GCP/Azure).
• Excellent in your verbal and written communication skills; comfortable with and effective at delivering presentations.
• Self-driven with the capability to lead projects and perform efficiently independently and as part of a team.

Working at PIPL