Key Responsibilities:

Develop and implement predictive models and algorithms using statistical and machine learning techniques, such as regression, clustering, classification, and neural networks.
Collaborate with Data Scientists and Business Analysts to understand business needs and translate them into technical requirements.
Clean, transform, and analyze large datasets to identify patterns and trends that can be used for predictive modeling.
Create and maintain data pipelines to ensure the accuracy and reliability of data being used for predictive analytics.
Test and validate predictive models to ensure their effectiveness and make necessary adjustments to improve their performance.
Develop and maintain dashboards and reports to communicate the results of predictive models to stakeholders.
Monitor and track the performance of predictive models and make necessary updates and enhancements to keep them relevant and up-to-date.
Keep up-to-date with the latest industry trends and best practices in predictive analytics and machine learning to continuously improve our processes and techniques.

Qualifications:

Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, or a related field.
Minimum of 3 years of experience in predictive analytics or data science.
Strong knowledge of statistical and machine learning techniques and tools, such as R, Python, SQL, and SAS.
Experience with data cleaning, transformation, and manipulation.
Proven experience in developing and implementing predictive models and algorithms.
Experience with data visualization and reporting tools.
Strong analytical and problem-solving skills.
Excellent communication and collaboration skills.
Ability to work in a fast-paced and dynamic environment.
Attention to detail and ability to work with large datasets.
Knowledge of big data technologies, such as Hadoop, Spark, and NoSQL databases, is a plus.

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