Data Scientist

Responsibilities

• Collect, process, and analyse large datasets to identify trends, patterns, and insights that inform business strategies.
• Develop and deploy predictive models using statistical, machine learning, and deep learning techniques.
• Work closely with stakeholders to understand their data needs and translate business requirements into analytical solutions.
• Build and maintain data pipelines to ensure data quality and accessibility for analysis.
• Perform exploratory data analysis (EDA) to uncover key insights and guide decision-making.
• Present findings and recommendations to both technical and non-technical audiences through reports, dashboards, and presentations.
• Collaborate with data engineers and software developers to integrate analytical solutions into production systems.
• Stay current with the latest developments in data science and machine learning and apply new techniques as appropriate.
• Contribute to the development and implementation of best practices for data analysis, modelling, and reporting.
  

Requirements

• Bachelor's or Master's degree in Data Science, Statistics, Computer Science, Mathematics, or a related field.
• At least 3 years of professional experience in data science or a related role.
• Proficiency in programming languages such as Python or R.
• Strong knowledge of statistical analysis, machine learning algorithms, and data visualisation tools.
• Experience with data manipulation and analysis using libraries such as Pandas, NumPy, and Scikit-learn.
• Familiarity with data visualisation tools such as Tableau, Power BI, or Matplotlib.
• Experience with SQL and NoSQL databases for data extraction and manipulation.
• Understanding of cloud platforms like AWS, Azure, or Google Cloud is a plus.
• Strong problem-solving skills and the ability to work independently and in a team.
• Excellent communication skills, with the ability to convey complex technical concepts to a non-technical audience.
• Detail-oriented with a focus on delivering high-quality, accurate work.
• Experience with big data technologies such as Hadoop, Spark, or Kafka.
• Knowledge of deep learning frameworks like TensorFlow or PyTorch.
• Experience with A/B testing and experimental design.
• Familiarity with version control systems such as Git.