Overview
On Site
Depends on Experience
Contract - W2
Skills
Design thinking
Communication
Computer science
Data
Database
Databricks
Design
Artificial intelligence
Business requirements
C
C#
C++
Cloud computing
Agile
Algorithms
Google Cloud Platform
Graph databases
Hierarchical clustering
Econometrics
Ensemble
Financial services
Good Clinical Practice
Governance
Amazon Web Services
Microsoft Azure
Natural language processing
Network
Analytical skill
Analytics
Process control
Python
Regulatory Compliance
Scala
Apache Hive
Documentation
Machine Learning (ML)
Software development methodology
Technical writing
Unstructured data
Visualization
XGBoost
Neural Network
Pandas
R
Science
Software development
Statistics
Torch
matplotlib
scikit-learn
Job Details
Short Description
Drive innovative AI/ML solutions across the firm through modern AI/ML architecture & engineering practices.
Description
Job Responsibilities
- Analyze complex/unstructured data to understand the business problem and use case
- Analyze business requirements, design, and develop appropriate methodology
- Develop deployable, scalable and effective models/ analytical methods as part of technology managed system or as a self-served application of a business user
- Work collaboratively and creatively with other data scientists, technology partners, risk professionals, model validation teams, etc.
- Prepare technical documentation of quantitative models for internal model risk and governance review
Required qualifications, capabilities, and skills
- 6+ years of related experience in Python, R or Scala with Bachelor of Science degree in Computer Science, Physical Sciences, Econometrics, Statistics, or other any quantitative discipline.
- Demonstrable theoretical and application knowledge of Machine Learning methods, and/or Statistical Models
- Demonstrable hands-on experience and familiarity with any or all of the following packages, algorithms, and/or alternatives, including Graph Learning Packages : (NetworkX, Torch-Geometric, Graphframes, Graphistry),ML Packages (Pandas, Scikit-Learn, XGBoost, catboost, lightgbm, automl, Optuna, Hyperopt), Visualization Packages (Matplotlib, Seaborn, Geopandas), Algorithm (Ensemble Louvian / Hierarchical Clustering, Label Propagation, Connected Component Analysis, Graph Neural net (Graph Attention Network), Page Rank, Centrality Analysis, Tree based Analysis, Outlier Detection Methods, Zero Shot/ Few Shot learning)
- Demonstrable experience with graph analytics, graph-based learning, and graph representation/visualization
- Experience in graph Database: TigerGraph, Neo4j
- Experience in Query Language: Hive, Cypher (Graph Query Language)
- Hands-on professional experience in software development especially with analytical & computationally intensive systems, digital transformations leveraging cloud technologies (AWS, Google Cloud Platform, Azure, Databricks etc.)
- Experience in developing and operationalization of data pipelines
- Familiarity and experience of assimilating large amounts of data from multiple databases and utilize them for creating actionable outcome; Adhering to a standardized analysis and project methodology; and Documenting quantitative analysis
Preferred qualifications, capabilities, and skills
- Post graduate degrees such as Master s Degree, PhD, etc. is preferred
- Working knowledge of C/C#/C++ or others is a plus
- Real life exposure to Agile SDLC, ModelOps and /Or Design Thinking is desirable.
- Familiarity with Natural Language Processing techniques is a plus
- Self-starter and strong influencing skills with strong communication skills
- Experience in financial services industry and/ or, experience with process, controls and governance of a highly regulated environment
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.