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Metro location, mid-level generalist Data Scientist role, broad ML skillset create high applicant competition.
Core ML, Python, and deployment skills are transferable, but financial-services context adds moderate specialization.
Explicit 3–4 years requirement plus mandatory Python, ML frameworks, and SQL increases shortlisting strictness.
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Develop, train, and deploy machine learning and predictive models addressing complex business problems.
Collect, clean, analyze diverse data types, perform exploratory data analysis, and translate findings into actionable business insights.
Collaborate with stakeholders and data engineers to build scalable data science solutions and communicate insights through visualizations and dashboards.
3-4 years of experience in Data Science, Machine Learning, or Advanced Analytics.
Strong proficiency in Python and experience with libraries like Pandas, NumPy, Scikit-learn, Matplotlib/Plotly, and Jupyter Notebook.
Experience with SQL and database querying; knowledge of data preprocessing and data wrangling techniques.
Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, AI, Engineering, or related field.
Proven ability to build and improve predictive and classification models in business contexts using statistical and machine learning techniques.
Experience working cross-functionally with business teams and data engineering to design and deploy scalable analytical solutions.
Familiarity with advanced AI topics like Generative AI, LLMs, cloud AI platforms, deep learning frameworks, and MLOps is advantageous but not mandatory.