We are looking for Big Data Architect for our client in New York City, NY
Job Title: Big Data Architect
Job Location: New York City, NY
Job Type: Contract ? 12 Months / Contract to Hire / Direct Hire
- The Compliance Technology of client is building next gen surveillance model for risk mitigation and requires a big data architect who has broad knowledge of the current machinelearning and statistical modeling methods and an understanding of how such methods are applied to compliance, specifically in Financial Services Industry.
- This role requires broad knowledge of the current machine learning and statistical modeling methods and an understanding of how such methods are applied to trader and employee compliance, specifically in Financial Services Industry. This is a complex, multi-functional, cross-platform domain which will require expertise in the data science
- Experience in manipulating large datasets
- Demonstrable significant experience in leading manipulation of large datasets to successful conclusions
- Strong Programming skills (such as Hadoop MapReduce or otherbig data frameworks)
- Experience with Statistical modeling (like Jupyter, python or R)
- Relevant experience working in the Financial Services industry
- Proficiency in statistical analysis ,quantitative analytics, forecasting/predictive analytics
- Creating automated anomaly detection systems and constant tracking of its performance
- Identifies what data is available and relevant, including internal and external data sources, leveraging new data collection processes such as smart meters
- Degree in Mathematics, Statistics, Computer Science, Operations Research, Physics or otherquantitative discipline like Financial engineering.
- 3-5years of relevant quantitative and qualitative research and analytics experience.
- 3+ years of experience in building machine models in R, Python or SAS , using techniques such as Random Forest, ANN, SVM, logistic regression.
- Hands-on expertise with SQL databases such as Oracle is required.
- Knowledge of implementing streaming models (dynamic / incremental models) such as streaming K-means and Streaming Random Forest is desired.