Data Scientist

ESQ Business Services, LLC
yesterday

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Intermediate

Job location

Remote

Tech stack

Agile Methodologies
Algorithm Design
Amazon Web Services (AWS)
Azure
Data Mining
Relational Databases
Python
Linear Regression
Logistic Regression
Machine Learning
Natural Language Processing
Recommender Systems
Standard Sql
Support Vector Machine
Google Cloud Platform
Large Language Models
Spark
Deep Learning
Information Technology

Job description

  1. Utilize advanced algorithms and data mining techniques to build personalized recommendation systems, optimizing product and service recommendations to enhance user experience and improve business conversion rates.

  2. Conduct precise analysis of probability distributions in casino games, develop and validate mathematical models to ensure game fairness and risk control, supporting compliance operations and decision-making.

  3. Continuously explore and implement various applications of LLMs in business, from natural language processing to intelligent customer service and content generation, driving enterprises toward intelligent transformation.

  4. Work closely with various business units, leveraging data analysis and visualization tools to promote a data-driven decision-making culture, helping departments uncover insights from data and develop effective strategies.

Requirements

  • Ability to come up with sound research designs and make methodological choices to address business problems with appropriate statistical and machine learning models
  • 2+ years of experience as a data scientist, quantitative researcher, quantitative analyst or another relevant role
  • Degree in Applied Mathematics, Computer Science, Financial Engineering, Technology or Engineering
  • Knowledge of probability theory, inferential statistics, machine learning, Bayesian statistics, linear algebra, and numerical methods
  • Experience with statistical and machine learning models, such as regression-based models (e.g., logistic regression, linear regression, negative binomial regression), tree-based models (e.g., random forests), support vector machines, PCA, clustering models, matrix factorization, deep learning, etc
  • Experience using statistical and machine learning models to contribute to company growth efforts, impacting revenue and other key business outcomes
  • Advanced understanding of Python and the quantitative analysis ecosystem in Python
  • Knowledge of SQL and experience with relational databases
  • Agile, action-oriente

Nice to have

  • Apache Spark
  • Experience working in cloud platforms (AWS, GCP, Microsoft Azure)
  • Relevant knowledge or experience in the gaming industry
  • Solid computer science background

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