Data Scientist
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Key skills for this role
About the Role
Genius HRTech Dubai is seeking a Data Scientist to leverage large datasets, build predictive models, and drive data-informed decisions. The role involves developing machine learning models, performing exploratory data analysis, and collaborating with cross-functional teams.
Key Skills for This Role
Responsibilities
- Develop, implement, and validate machine learning models and algorithms to solve complex business problems, such as fraud detection, customer churn prediction, recommendation systems, and demand forecasting.
- Clean, preprocess, and transform large, complex datasets from various sources (e.g., SQL databases, data lakes, APIs) to ensure data quality and readiness for analysis.
- Perform extensive exploratory data analysis (EDA) to identify trends, patterns, correlations, and anomalies, and generate actionable insights.
- Design, execute, and analyze A/B tests and other experimental designs to evaluate the impact of new features, products, or strategies.
- Collaborate with cross functional teams, including product managers, software engineers, and business stakeholders, to understand requirements, define project scopes, and deliver data driven solutions.
- Build and maintain robust data pipelines, integrate models into production systems, and monitor model performance over time.
- Create compelling data visualizations, dashboards, and reports to present complex analytical findings and recommendations to both technical and non technical audiences.
- Stay up to date with the latest advancements in data science, machine learning, artificial intelligence, and big data technologies.
- Mentor junior data scientists, share best practices, and contribute to the continuous improvement of the team's data science capabilities and tools.
- Evaluate and recommend new technologies, methodologies, and statistical approaches to enhance data analysis and modeling processes.
- Document methodologies, assumptions, and results clearly and concisely to ensure reproducibility and transparency.
Requirements
- Develop, implement, and validate machine learning models and algorithms
- Clean, preprocess, and transform large, complex datasets
- Perform exploratory data analysis (EDA)
- Design, execute, and analyze A/B tests
- Collaborate with cross functional teams
- Build and maintain robust data pipelines
- Create data visualizations and dashboards
- Stay up to date with latest advancements in data science
- Mentor junior data scientists
Full Job Posting
Overview
- We are seeking a highly skilled and passionate Data Scientist to join our innovative team.
- The ideal candidate will be responsible for leveraging large datasets to uncover insights, build predictive models, and drive data informed decision making across various business functions.
- You will work closely with product, engineering, and business teams to define problems, develop analytical solutions, and communicate findings effectively.
- This role requires a strong foundation in statistics, machine learning, and programming, along with excellent problem solving abilities.
Responsibilities
- Develop, implement, and validate machine learning models and algorithms to solve complex business problems, such as fraud detection, customer churn prediction, recommendation systems, and demand forecasting.
- Clean, preprocess, and transform large, complex datasets from various sources (e.g., SQL databases, data lakes, APIs) to ensure data quality and readiness for analysis.
- Perform extensive exploratory data analysis (EDA) to identify trends, patterns, correlations, and anomalies, and generate actionable insights.
- Design, execute, and analyze A/B tests and other experimental designs to evaluate the impact of new features, products, or strategies.
- Collaborate with cross functional teams, including product managers, software engineers, and business stakeholders, to understand requirements, define project scopes, and deliver data driven solutions.
- Build and maintain robust data pipelines, integrate models into production systems, and monitor model performance over time.
- Create compelling data visualizations, dashboards, and reports to present complex analytical findings and recommendations to both technical and non technical audiences.
- Stay up to date with the latest advancements in data science, machine learning, artificial intelligence, and big data technologies.
- Mentor junior data scientists, share best practices, and contribute to the continuous improvement of the team's data science capabilities and tools.
- Evaluate and recommend new technologies, methodologies, and statistical approaches to enhance data analysis and modeling processes.
- Document methodologies, assumptions, and results clearly and concisely to ensure reproducibility and transparency.
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