As a Data Scientist, you will play a pivotal role in developing and deploying sophisticated models to solve complex business problems. Your expertise in mathematics, statistics, and machine learning will be crucial in building predictive and rule-based models that deliver actionable insights. You will work closely with cross-functional teams to understand business requirements and translate them into data-driven solutions.

Key Responsibilities:
- Develop, implement, and maintain predictive and rule-based models to support business decision-making.
- Conduct thorough data analysis and feature engineering to prepare data for modeling.
- Apply advanced statistical and machine learning techniques to build and validate models.
- Collaborate with stakeholders to understand business needs and provide data-driven recommendations.
- Communicate findings and insights to non-technical stakeholders through clear and concise reports and presentations.
- Monitor model performance and make necessary adjustments to ensure accuracy and reliability.
- Stay updated with the latest advancements in data science and machine learning to continuously improve model quality.
- Work with data engineers to ensure data infrastructure and pipelines are optimized for model development and deployment.

Requirements:
- Bachelor's or Master's degree in Data Science, Statistics, Mathematics, Computer Science, or a related field. PhD is a plus.
- Proven experience as a Data Scientist or in a similar role, with a strong portfolio of successfully developed models.
- Proficiency in programming languages such as Python or R.
- Strong understanding of machine learning algorithms, statistical methods, and data mining techniques.
- Experience with data manipulation and analysis using libraries such as pandas, NumPy, and scikit-learn.
- Familiarity with deep learning frameworks such as TensorFlow or PyTorch is a plus.
- Expertise in SQL for data extraction and manipulation.
- Solid understanding of data preprocessing, feature selection, and feature engineering techniques.
- Experience with model deployment and monitoring in a production environment.
- Strong problem-solving skills and the ability to think critically and analytically.
- Excellent communication skills, with the ability to explain complex concepts to non-technical stakeholders.
- Ability to work collaboratively in a team environment and manage multiple projects simultaneously.

Preferred Qualifications:
- Experience with big data technologies such as Hadoop, Spark, or similar.
- Knowledge of cloud platforms such as AWS, Azure, or Google Cloud for data storage and model deployment.
- Familiarity with version control systems like Git.
- Experience with A/B testing and experimental design.
- Understanding of business intelligence tools such as Tableau, Power BI, or similar.