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Matchworkers International

Data Scientist (UK Relocation)

Matchworkers International
United Arab Emirates · Full-time · Mid-Senior

Amazing opportunity to relocate to UK as a Data Scientist. This position is for one of our major clients in UK. If your application is successful, the employer will sponsor your Work Visa to the UK. This is a full-time on-site role.


Role: Data Scientist


Position Overview:

We are seeking a highly skilled and motivated Data Scientist to join our team. In this role, you will analyze large datasets, develop predictive models, and provide data-driven insights that help drive business strategies and decisions. You will work closely with cross-functional teams to transform raw data into actionable solutions, ensuring the quality and accuracy of the information provided.


Key Responsibilities:

  • Data Analysis & Modeling:
  • Analyze large datasets to extract meaningful insights and identify trends, patterns, and opportunities.
  • Develop and implement statistical models, machine learning algorithms, and data mining techniques to address business challenges.
  • Perform exploratory data analysis (EDA) to understand data characteristics and improve model accuracy.
  • Predictive Modeling & Machine Learning:
  • Build, test, and deploy predictive models (supervised, unsupervised, or deep learning) to forecast outcomes and inform decision-making.
  • Apply advanced algorithms to solve complex business problems such as customer segmentation, demand forecasting, recommendation engines, and anomaly detection.
  • Data Visualization & Reporting:
  • Create clear, actionable visualizations and dashboards to present analytical findings to stakeholders using tools like Tableau, Power BI, or custom visualizations.
  • Communicate complex statistical concepts and results to non-technical audiences, ensuring insights are easily understood and applicable.
  • Data Management & Cleaning:
  • Ensure data quality by cleaning, transforming, and validating datasets to prepare them for analysis.
  • Work with data engineering teams to integrate and optimize data pipelines and storage solutions.
  • Collaboration & Stakeholder Engagement:
  • Collaborate with business stakeholders to understand data needs and translate them into actionable analyses and models.
  • Work with software engineers, product managers, and other team members to deploy models into production environments.
  • Research & Development:
  • Stay up-to-date with the latest trends, technologies, and best practices in data science, machine learning, and AI.
  • Contribute to ongoing improvements in tools, techniques, and processes for data analytics.


Required Qualifications:

  • Education:
  • Bachelor’s degree in Computer Science, Mathematics, Statistics, Engineering, Economics, or a related field (Master’s or Ph.D. is a plus).
  • Experience:
  • 2+ years of experience in data science, machine learning, or related roles.
  • Proven track record of developing and deploying data-driven solutions in a business setting.
  • Hands-on experience with programming languages such as Python, R, or similar.
  • Familiarity with big data tools (e.g., Hadoop, Spark) and cloud platforms (e.g., AWS, GCP, Azure) is a plus.
  • Skills:
  • Strong proficiency in statistical analysis, hypothesis testing, and modeling.
  • Experience with machine learning libraries such as scikit-learn, TensorFlow, PyTorch, etc.
  • Ability to work with large datasets and relational databases (SQL, NoSQL).
  • Expertise in data visualization tools (e.g., Tableau, Power BI, matplotlib, Seaborn).
  • Excellent problem-solving and analytical skills, with attention to detail.

Key Skills

Ranked by relevance

c machine learning ha data visualization data analysis power bi tableau sql cis ai ui product manager deep learning data mining tensorflow matplotlib big data storage pytorch seaborn python hadoop nosql unity cloud excel spark aws gcp esp sla lan oop das
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Posted
Nov 15, 2024
Type
Full-time
Level
Mid-Senior
Location
Dubai

Industries

Technology Information Media

Categories

Information Technology

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