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Home UAE Senior Data Scientist

Senior Data Scientist

Full time at Hays in UAE
Posted on February 7, 2025

Job details

Roles and Responsibilities

1. Data Strategy & Leadership
  • Project Leadership : Leading data science projects from ideation to deployment. This includes managing project timelines, resources, and ensuring alignment with business goals.
  • Mentoring & Coaching : Guiding and mentoring junior data scientists and data analysts to help them grow in their roles. This involves providing technical guidance, reviewing work, and offering professional development advice.
  • Stakeholder Collaboration : Working closely with business stakeholders (e.g., marketing, finance, product teams) to understand their objectives and translate them into data-driven solutions.
  • Strategic Input : Providing strategic recommendations based on data analysis and insights to help drive business decisions and long-term goals.
2. Advanced Data Analysis & Modeling
  • Data Preprocessing : Overseeing data collection, cleaning, transformation, and feature engineering to ensure the data is prepared for analysis and modeling.
  • Machine Learning : Building and deploying machine learning models for tasks such as classification, regression, clustering, or recommendation systems. This includes supervised and unsupervised learning, deep learning, and ensemble methods.
  • Statistical Analysis : Applying statistical methods to identify patterns, test hypotheses, and validate models. This could include A/B testing, hypothesis testing, and time-series analysis.
  • Big Data Technologies : Leveraging big data tools and frameworks like Hadoop , Spark , or Google BigQuery to analyze large datasets that cannot be handled by traditional systems.
  • Model Optimization : Tuning models for better performance by adjusting hyperparameters, experimenting with different algorithms, and applying cross-validation techniques.
3. Data Visualization & Reporting
  • Data Visualization : Creating clear, intuitive, and interactive visualizations to communicate complex data findings. This can include using tools like Tableau , Power BI , Matplotlib , Seaborn , or Plotly .
  • Dashboard Development : Designing and maintaining dashboards that track key performance indicators (KPIs) and provide stakeholders with real-time data insights.
  • Report Generation : Preparing detailed reports and presentations to communicate insights, model results, and business recommendations to both technical and non-technical stakeholders.
4. Advanced Statistical & Mathematical Techniques
  • Statistical Modeling : Applying advanced statistical techniques (e.g., linear regression, logistic regression, Bayesian analysis, etc.) to interpret data and derive business insights.
  • Optimization & Simulation : Using optimization techniques (e.g., linear programming, Monte Carlo simulations) for decision-making and resource allocation.
  • Deep Learning : Designing and implementing deep learning models for more complex tasks like image recognition, natural language processing (NLP), or autonomous systems.
5. Product Development & Deployment
  • Model Deployment : Overseeing the deployment of machine learning models into production environments and ensuring they are scalable, maintainable, and integrated with other systems (e.g., via AWS , Azure , or Google Cloud platforms).
  • Model Monitoring & Maintenance : Continuously monitoring the performance of deployed models, troubleshooting issues, and improving models based on new data or feedback.
  • Collaboration with Engineering Teams : Working closely with data engineers and software developers to implement and scale models into production environments efficiently.
6. Research & Innovation
  • Staying Current : Keeping up-to-date with the latest developments in data science, machine learning, and AI, and exploring how these advancements can be applied to solve business problems.

Desired Candidate Profile

Technical Skills Required
  • Proficient throughout the Machine Learning life cycle
  • End to end development; creation to deployment
  • Cloud experience; AWS, Azure, GCP
  • MLOps
  • Data Engineering pipelines
  • Software Engineering experience is a bonus; Python or Java
Experience Required
  • Worked on products that have gone into real settings
  • Take end to end ownership of all ML features
  • Be able to implement key machine learning strategies across the business and work with stakeholders effectively
  • Be able to collaborate, communicate effectively and coordinate end to end delivery
Education Experience
  • PhD or MSc is highly desirable (STEM; Com Sci, Maths, Statistics, Fin Maths, Physics etc.)
What You'll Get in Return
  • Visa
  • Medical benefits + family
  • Loans and credit facilities available
  • Yearly Bonus
  • Relocation allowance (cash)
  • Return flight tickets yearly
  • Hotel stay paid for when first arrive in the country
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