Data Scientist

Splash Software; Dubai; On-site; AED 200,000 - 300,000; Full time

Job summary

A leading software company is seeking an experienced Data Scientist to join their team in Dubai. This role focuses on driving data-driven decision-making in the Online Gaming Industry through advanced analytics and machine learning. The ideal candidate will have a Master’s degree in Mathematics or Statistics and proven experience in building machine learning models. Responsibilities include designing models, analyzing datasets for insights, and collaborating with teams to enhance business performance. Excellent communication skills are essential for translating data findings for stakeholders.

Qualifications

• Proven experience building and deploying machine learning models.
• Strong knowledge of statistical methods, data modeling, and hypothesis testing.
• Excellent communication skills for non-technical stakeholders.

Responsibilities

• Design and implement machine learning models for trend prediction.
• Analyze datasets to identify optimization opportunities.
• Create and present data-driven insights to stakeholders.
• Deploy and monitor models in production environments.

Skills

Machine learning expertise

Data analysis

Statistical techniques

Python or R proficiency

Experience in Online Gaming Industry

Problem-solving skills

Education

Masters degree in Mathematics or Statistics

Tools

Python

R

Pandas

NumPy

TensorFlow

PyTorch

Elasticsearch

SQL

Kibana

Tableau

Job description

We are seeking a highly motivatedData Scientist with extensive experience in Online Gaming Industryto join our team and drive data-driven decision-making through advanced analytics and machine learning models. The ideal candidate will have a strong technical background, a passion for uncovering insights from complex datasets, and the ability to collaborate with cross-functional teams to solve business challenges.

Key Responsibilities

• Design and implement machine learning models to predict trends, detect anomalies, and uncover actionable insights.
• Analyze structured and unstructured datasets to identify patterns and opportunities for optimization.
• Develop predictive models and algorithms for key business use cases, such as risk management, forecasting, and segmentation.
• Collaborate with data engineers and analysts to ensure data readiness for analysis and model deployment.
• Use statistical techniques to validate hypotheses, assess model performance, and improve decision-making processes.
• Create and present data-driven insights and recommendations to stakeholders in a clear and compelling manner.
• Deploy, monitor, and refine models in production environments to ensure scalability and reliability.
• Stay updated on the latest advancements in data science and machine learning, incorporating best practices into projects.

Qualifications

• Masters degree in Mathematics or Statistics.
• Proven experience as a Senior Data Scientist, with expertise in building and deploying machine learning models.
• Proficiency in Python or R, with experience in data manipulation libraries (e.g., Pandas, NumPy) and machine learning frameworks (e.g., Scikit-learn, TensorFlow, PyTorch).
• Strong knowledge of statistical methods, data modeling, and hypothesis testing.
• Experience working with large-scale data in environments such as Elasticsearch or SQL databases.
• Familiarity with data visualization tools (e.g., Kibana, Tableau, or Matplotlib) for presenting insights.
• Excellent problem-solving and analytical skills with attention to detail.
• Strong communication skills, with the ability to translate complex data findings into actionable insights for non-technical stakeholders.
• Experience in the Online Gaming Industry is a Must.

Preferred Skills

• Hands-on experience with anomaly detection and forecasting models.
• Knowledge of big data tools and frameworks (e.g., Hadoop, Spark).
• Familiarity with MLOps practices and tools for deploying and managing machine learning models in production.
• Experience with cloud platforms (e.g., AWS, Google Cloud, Azure) for data science workflows.
• Understanding of Elasticsearchs machine learning capabilities is a plus.