Job Location: Noida
C2FO is working to deliver a future where every company in the world has the capital it needs to grow. Our technology provides an easy, low-cost way for businesses of all sizes to increase cash flow by receiving early invoice payments. Since 2008, C2FOs online platform and innovative financial products have accelerated payments by more than $1 billion in working capital each week for companies in over 180 countries.
Named one of Forbes Fintech 50, C2FO provides more than $1 billion in working capital each week for hundreds of thousands of businesses. C2FO has more than 800 employees worldwide, headquartered in Kansas City, and operations throughout Europe, India, Asia Pacific, and Australia. For more information, visit www.C2FO.com.
About the Data and Decision Science team:
The Data & Decision Science (D&DS) team is the most fluid and dynamic team at C2FO. At any given time, the members of the department contribute to multiple projects. It consists of the Data Engineering, Data Science and Analytics, Data Operations, and Business Intelligence teams.
As an organization, C2FO believes that data is the lifeblood for any technology-based company. Our Data teams use cutting edge, open source technologies to collect, process, store, and leverage data. The D&DS team is responsible for C2FOs end-to-end data solutions, focusing on data architectures, data science and machine learning, business intelligence and analytics, and overall data strategy.
Empowered by the flexibility of cloud-based hosted computing, and spread across India and US, collectively, these teams are responsible for leveraging both internal and external data that helps C2FO innovate, take data backed decisions, and solve complex business problems such as customer acquisition and retention.
About the role
Designation: Data Scientist
Years of experience: 2 to 5 years
As a Data Scientist at C2FO, you will analyze, model, implement and automate scalable solutions for our customers. You have the opportunity to embed your creativity with an array of ML algorithms in addition with domain knowledge to solve complex business problems like customer acquisition and retention. Successful candidates will be a part of a talented team thats disrupting working capital around the world.
Data Scientists at C2FO are adaptable problem solvers who show a strong understanding of basic ML and Statistics principles and can execute with little or no supervision. They are astute and pragmatic – they have a strong ability to build MVP solutions and iterate quickly on complex business problems. They have a strong hustler attitude; when they meet a roadblock, they can identify individuals or teams who may help them and then reach out to those resources without prompting.
- Exploit various ML techniques to build models for various business problems such as Entity Matching, Forecasting, Credit Scoring, Attrition modeling etc
- Analyze, extract, and optimize relevant information from large amounts of data and deliver insightful analysis that will drive business decisions on product features and operational efficiency
- Establish scalable, efficient processes for data analyses, model development, validation and experimentation
- Work with cross functional teams to understand business opportunities and turn research into products
- Partner with Data Engineering and Data Governance teams to put together a data validation framework and establish processes that ensure data quality and integrity requirements are met
- 2 to 5 years of relevant work experience; nice to have: prior experience working in finance
- Solid grasp of mathematics and machine learning concepts (i.e., optimization functions, linear algebra, etc.)
- Knowledgeable of relevant literature around applications for machine learning and deep learning
- Hands on experience in building machine learning solutions from conceptualization to implementation; experience deploying models in a production environment
- Strong knowledge of supervised (classification, regression) and unsupervised techniques (clustering, dimensionality reduction)
- Experience with experimentation and hypothesis testing
- Proficient in Python; any additional programming language is a big plus
- Fluency in data manipulation (SQL, Spark, Pandas)
- Experience with machine learning tools such as scikit-learn, XGBoost, Pytorch
- Strong problem solving and communication skills
- Curiosity. A repeated pattern asking and understanding the “why” behind the data