Job Description

Salary: Open

Summary of Position:
We are looking for a talented and motivated data scientist experienced in working directly with clients, managers, and technical staff to understand business needs, develop technical plans, and deliver data-driven analytical solutions that solve client problems. This role will assist the client in integrating data analytics into their daily operations. You will create and deploy predictive models from a variety of data sources and types using the latest mathematical and statistical methods. You will also have the freedom to grow a team to support the client's data analytics needs.



Job Specifications/Requirements:

• Six (6) years of relevant experience in applied research, big data analytics, statistics, applied mathematics, data science, computer science, operations research or other closely related other quantitative or mathematical discipline. At least three (3) years of direct experience in machine learning.
• Advanced Degree (Masters or PhD) in Statistics, Applied Mathematics, Data Science, Computer
• Science, Operations Research or other closely related other quantitative or mathematical discipline. A PhD degree may be substituted for up to three (3) years of relevant experience.
• Demonstrates knowledge of data mining methods, databases, data visualization and machine learning.
• Ability to communicate analysis techniques, concepts and products.
• Ability to develop data-driven solutions, data models, and visualizations

Desired Skills

• Experience building AI/ML solutions from large JSON data stores
• Experience with graph technologies and tools
• Experience with analysis and visualization of worldwide data flows
• Experience in developing algorithms in support of fraud detection
• Familiarity with Databricks or similar cloud-based distributed database technologies
• Familiarity with PySpark and Python
• Comfortable developing complex SQL queries to extract, transform, and load data
• Experience with analytic techniques such as Anomaly detection, Clustering, and Time-series (e.g., ARIMA)
• Experience implementing NLP concepts including preprocessing (stemming, etc.), TF-IDF, Named Entity Recognition, and LLMs.

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