Lead Data Scientist

DUTIES: Conducting comprehensive analysis of telecommunications data to discern patterns, trends, and anomalies, employing statistical methods and machine learning techniques. Developing and refining predictive models to anticipate potential network issues and enhance customer experience. Collaborating with cross-functional teams to gather domain knowledge and integrating it into model development processes. Evaluating model performance using appropriate metrics and refine models iteratively to achieve desired outcomes. Communicating findings and insights to stakeholders through clear and concise presentations and reports. Leading the feature engineering process to extract relevant information from raw data, considering both domain expertise and algorithmic insights. Creating new features and transform existing ones using advanced techniques such as dimensionality reduction and feature scaling. Employing statistical methods and domain knowledge to select the most informative features for model training, ensuring model interpretability and performance. Collaborating with domain experts to validate feature-engineering approaches and refining feature sets based on business requirements. Overseeing the training and optimization of predictive models, selecting appropriate algorithms and hyperparameters based on data characteristics and business objectives. Utilizing techniques such as cross-validation and ensemble learning to improve model generalization and robustness. Implementing advanced optimization algorithms, including gradient boosting and Bayesian optimization, to fine-tune model performance. Developing strategies for handling imbalanced data and mitigating overfitting, ensuring model reliability in real-world scenarios. Establishing protocols for model maintenance and retraining to adapt to evolving data and business needs. Leading the deployment of predictive models into production environments, collaborating with IT teams to ensure seamless integration and scalability. Developing monitoring systems to track model performance and detect deviations from expected behavior, implementing automated alerting mechanisms for timely intervention. Establishing governance processes to manage model lifecycle, including version control, documentation, and model retraining. Conducting regular audits and evaluations to assess model effectiveness and compliance with regulatory requirements. Engaging with stakeholders to gather feedback and insights from model users, facilitating continuous improvement and optimization efforts. Fostering a collaborative environment by actively engaging with cross-functional teams, sharing expertise, and aligning on project objectives and priorities. Contributing to knowledge sharing initiatives by documenting best practices, lessons learned, and case studies to facilitate learning and development within the organization. Staying abreast of industry trends, research advancements, and emerging technologies in data science and telecommunications, leveraging this knowledge to drive innovation and enhance project outcomes.

REQUIRED EXPERIENCE: Requires a Master's degree in Data Science, Computer Science, Information Technology, Engineering, Computer Information Systems or related, plus 1 year of experience in job offered or related occupations of Senior Data Scientist, Data Scientist, Programmer Analyst or related. Duties entail work with Python, Neo4j, Oracle SQL Developer, Tableau, Unix, Shell Scripting and Cypher.