Key Responsibilities :
- Data Analysis and Modeling : Develop, implement, and refine advanced statistical models and machine learning algorithms to solve business problems and identify opportunities for improvement.
- Data Engineering : Collaborate with data engineers to design and optimize data pipelines, ensuring data quality, integrity, and accessibility for analysis.
- Insights Generation : Interpret complex data sets, identify trends and patterns, and present actionable insights through clear and compelling visualizations and reports.
- Collaboration : Work closely with cross-functional teams, including product managers, engineers, and business leaders, to understand requirements and deliver data-driven solutions that support strategic goals.
- Project Management : Lead and manage data science projects from inception to completion, ensuring timely delivery and alignment with business objectives.
- Mentorship : Provide guidance and support to junior data scientists and contribute to the development of best practices and methodologies within the team.
- Innovation : Stay current with industry trends, emerging technologies, and advancements in data science to continuously enhance methodologies and tools used within the organization.
Qualifications :
- Education : Bachelor's degree in Data Science, Statistics, Computer Science, Mathematics, or a related field. Advanced degree (Master’s or PhD) is a plus.
- Experience : Minimum of 5 years of experience in data science or a related role, with a proven track record of applying advanced analytics to solve complex business problems.
- Technical Skills : Proficiency in programming languages such as Python or R, and experience with data manipulation libraries (e.
g., Pandas, NumPy). Knowledge of machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch) and experience with SQL and data visualization tools (e.
g., Tableau, Power BI) is essential.
- Analytical Skills : Strong quantitative and analytical skills, with the ability to develop and interpret statistical models and algorithms.
- Communication : Excellent communication and presentation skills, with the ability to convey technical information to non-technical stakeholders effectively.
- Problem-Solving : Demonstrated ability to approach complex problems with a strategic and data-driven mindset, and to develop innovative solutions.
Preferred Qualifications :
- Knowledge of cloud platforms (e.g., AWS, Azure, Google Cloud) and big data technologies (e.g., Hadoop, Spark).
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