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Talantir Hermitage, TN seeks a Data Scientist to support data acquisition, cleaning, preprocessing, and quality checks across internal and third‑party financial systems using SQL, Python (Pandas) and Excel.
You will conduct exploratory data analysis, build and validate models with Scikit-learn, and help automate data pipelines with Python and RPA tools. Collaboration with finance, data engineering, and strategy teams aligns insights with business goals.
Job Title : Data ScientistsLocation : Hermitage, TN
Assist in collecting, validating, and preprocessing structured and unstructured datasets from internal and third-party financial systems.Perform data quality checks, resolve anomalies, and maintain metadata using SQL, Python (Pandas), and Excel.
Conduct exploratory data analysis to identify trends, outliers, and correlations within financial and operational datasets.Support the preparation of data summaries, distribution checks, and hypothesis validations.
Assist in developing automation scripts and data pipelines using Python, Excel macros, and RPA tools (e.g., Blue Prism) to streamline data ingestion and transformation.Support version control and CI/CD practices using Git repositories.
Support senior data scientists in building and validating statistical and machine learning models to forecast revenue trends, customer churn, or financial health.Participate in refining time-series models and basic regressions using Python (Scikit-learn, StatsModels).
Contribute to financial modeling by evaluating key metrics (e.g., EBITDA, revenue growth, margins) and integrating external macroeconomic indicators into models.Work alongside business analysts to align technical models with stakeholder requirements.
Develop and maintain interactive dashboards using Tableau, Power BI, or Python (Matplotlib, Seaborn) to communicate insights to internal stakeholders.Automate reporting templates and visualization tools for monthly and quarterly updates.
Maintain comprehensive documentation for model assumptions, workflows, data dictionaries, and QA protocols.Ensure data practices align with internal governance policies and industry regulations (e.g., GDPR, SOX).
Work closely with cross-functional teams including finance, data engineering, and business strategy teams to align analytical efforts with organizational goals.Participate in sprint meetings and contribute to shared knowledge repositories.
Assist in tracking model performance and accuracy post-deployment using standard KPIs (e.g., RMSE, MAE).Help integrate user feedback and error analysis into model retraining cycles.
Attend internal workshops and training sessions on data science tools and methodologies.Stay informed of advancements in machine learning, financial modeling, and analytics platforms.