Understanding business problems and needs to design effective data science solutions
Gathering data from various sources, cleaning it appropriately, and visualizing it to identify anomalies and patterns
Developing robust predictive models using suitable modeling techniques
Generating insights and crafting a cohesive narrative from the data, summarizing analytical results, and presenting them to stakeholders
Collaborating with business partners to translate models into actionable business strategies
Working with IT to implement models into IT platforms for automated decision-making
Monitoring model performance to ensure effectiveness and validity
Continuously learning new technologies and refining skills daily
Requirements
Strong foundational knowledge in statistics, data science, and machine learning, including techniques such as multivariate regression, decision trees, stochastic gradient boosting, and deep learning
Proficiency in programming and working with open-source AI/ML languages and tools, including but not limited to SQL, Python, R, scikit-learn, statsmodels, XGBoost, and LightGBM
Proven experience in managing and analyzing large datasets
Excellent written and verbal communication skills, with the ability to convey complex ideas in a clear, business-oriented, and user-friendly manner
Self-motivated with a demonstrated ability to take initiative, identify opportunities for improvement, make actionable recommendations, and see them through to implementation while assessing their effectiveness
Outstanding interpersonal skills: approachable, tactful, and capable of influencing others, resolving conflicts, exercising sound judgment, maintaining confidentiality, and collaborating with all levels of the organization to build strong cross-functional partnerships
Tech Stack
Python
Scikit-Learn
SQL
Benefits
Competitive base pay and performance bonuses, dependent on role