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Data Scientist
Creative Chaos · Pakistan
About The Role
Job Brief
We are seeking a highly skilled Data Scientist to join our dynamic team. The ideal candidate will have a strong background in data analysis, machine learning, and statistical modeling. You will be responsible for analyzing large datasets to uncover trends and insights, building predictive models, and contributing to data-driven decision-making processes.
Duties and Responsibilities
- Lead the development and execution of data science projects, including problem formulation, data collection, analysis, modeling, and deployment of machine learning models.
- Collaborate with cross-functional teams to identify business opportunities and translate them into data science projects.
- Develop and implement machine learning algorithms and statistical models to solve complex business problems.
- Perform exploratory data analysis to gain insights and identify patterns in large and complex datasets.
- Work with data engineers to build robust and scalable data pipelines.
- Evaluate and validate models using appropriate performance metrics and statistical techniques.
- Present findings and insights to stakeholders in a clear and concise manner.
- Stay up-to-date with the latest advancements and best practices in data science and machine learning.
- Mentor and guide more junior data scientists in the team.
- Bachelors in Computer Science, Statistics, Mathematics, or a related field.
- 2-3 years of industry experience as a data scientist.
- Strong knowledge and experience in PowerBI, machine learning, statistical modeling, and data mining.
- Proficiency in Python or R for data analysis and modeling.
- Experience with big data technologies such as Hadoop, Spark, or SQL.
- Experience with deep learning frameworks such as TensorFlow or PyTorch is a plus.
- Strong problem-solving and critical-thinking skills.
- Excellent communication and presentation skills.
- Ability to work effectively in cross-functional teams.
- Strong attention to detail and ability to work on multiple projects simultaneously.
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