Key Responsibilities:

• Develop and implement machine learning models, algorithms, and statistical analysis to solve business challenges.
• Analyze large datasets to extract actionable insights and identify patterns or trends.
• Collaborate with product managers, engineers, and stakeholders to define project goals and data requirements.
• Lead the design, development, and deployment of predictive models to optimize business processes.
• Conduct A/B testing, data mining, and experimentation to support data-driven decision-making.
• Document and communicate data-driven insights and recommendations to non-technical stakeholders.
• Stay up-to-date with the latest trends and technologies in data science and machine learning.
• Mentor junior data scientists and data analysts within the team.

Qualifications:

• Bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field.
• Strong understanding of statistical analysis, machine learning, and data modeling.
• Proficiency in programming languages such as Python or R.
• Experience with data manipulation and analysis tools (e.g., pandas, NumPy, scikit-learn).
• Familiarity with data visualization tools (e.g., Tableau, Power BI, Matplotlib).
• Strong knowledge of SQL and database systems for data extraction.
• Excellent problem-solving skills and attention to detail.
• Good communication skills for presenting findings to both technical and non-technical audiences.

Preferred Skills:

• Experience with big data technologies (e.g., Hadoop, Spark) is a plus.
• Familiarity with cloud platforms (e.g., AWS, Google Cloud, Azure) for data science workflows.
• Knowledge of deep learning frameworks (e.g., TensorFlow, PyTorch) is advantageous.
• Prior experience working with A/B testing and experimental design.
• Any relevant certifications in data science or machine learning are a plus.