Junior Data Scientist
Regulatory DataCorp | Information Technology | King of Prussia, PA
RDC is looking for a Junior Data Scientist to augment our existing team. Responsibilities would include using data science techniques to improve RDC’s world-class risk and compliance protection services. We assist our global network of clients in identifying banned/suspected persons and organizations. We work towards strengthening fraud protection, ensuring regulatory compliance, managing supply and distribution risk, and protecting the brand equity of our clients.
We are looking for someone adept at using large data sets to find opportunities for product and process optimization. Candidates who have completed relevant coursework or an internship in data science are preferred. Experience using a variety of data tools, building and implementing models, using/creating algorithms, and creating/running simulations is all essential. The new hire will drive RDC's business results with their data-based insights and work with stakeholders to improve business outcomes. Our ideal candidate is someone comfortable working with other team members as well as independently.
- Assist the senior data scientists to identify opportunities for leveraging company data to drive business solutions using machine Learning/NLP
- Mine and analyze data from company databases to drive optimization and improvement of product development, marketing techniques and business strategies
- Assess the effectiveness and accuracy of new data sources and data gathering techniques
- Coordinate with different functional teams to design and deploy machine Learning/NLP models to production and maintain/monitor performance
- Train deep learning models with internal and external datasets
- 1 – 3 years of experience manipulating data sets and building statistical models either in academia or industry
- BS, MS or Ph.D. in one of the following disciplines: Statistics/Mathematics, Computer Science, Physics, or a closely related field
- Knowledge of advanced statistical techniques and concepts (model selection and hypothesis testing, statistical inference etc.) and experience applying them to real-world problems
- Knowledge of machine learning techniques (e.g. supervised, unsupervised, neural networks, deep learning) and their real-world advantages/drawbacks
- Understanding of natural language processing, information retrieval, and data mining techniques
- Experience with databases and big data tools such as Hadoop/Spark, MSSQL, MongoDB etc.
- Experience with data visualization tools, such as Matplotlib/Seaborn, ggplot, D3.js, Tableau etc.
- Fluent in Python, Scala, or R to manipulate and draw insights from large data sets
- Programming experience using languages with object-oriented features such as Java, C/C++.
- Can write clean and well documented code. Has good technical writing and verbal communication skills.