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Local Pandas Jobs in Tennessee (NOW HIRING)

Local Pandas information

What is the difference between Local Pandas vs Data Analysts?

AspectLocal PandasData Analysts
Required CredentialsProficiency in Python, pandas library, basic data skillsBachelor's in statistics, data science, or related field; sometimes certifications
Work EnvironmentData analysis, scripting, coding in Python, often remote or office-basedData interpretation, reporting, often in office or remote settings
Industry UsageTech, finance, healthcare, and more; used by data-focused teamsBusiness, marketing, finance, and other sectors requiring data insights

Local Pandas professionals focus on coding and data manipulation using Python, while Data Analysts often handle broader data interpretation and reporting. Both roles overlap in data skills but differ in technical depth and scope.

What are the most commonly searched types of Pandas jobs in Tennessee?

The most popular types of Pandas jobs in Tennessee are:

What are popular job titles related to Local Pandas jobs in Tennessee?

For Local Pandas jobs in Tennessee, the most frequently searched job titles are:

What cities in Tennessee are hiring for Local Pandas jobs?

Cities in Tennessee with the most Local Pandas job openings:

Infographic showing various Local Pandas job openings in Tennessee as of August 2026, with employment types broken down into 1% As Needed, 71% Full Time, 24% Part Time, and 4% Contract. Highlights an 97% Physical, 1% Hybrid, and 2% Remote job distribution.

$100 - $130/hr

Other

This job post has expired today. Applications are no longer accepted.


Job description

Job Description: We are seeking a highly skilled Senior Data Scientist with strong experience in cloud-based data platforms (Google Cloud or similar), Python/PySpark development, and advanced time‑series forecasting. The ideal candidate will have deep supply chain domain expertise—preferably in Demand Forecasting—and a proven track record of building, training, and operationalizing predictive models at scale. This role will also focus on identifying data anomalies, creating alerting frameworks, and improving model accuracy through metric evaluation and tuning.

Key Responsibilities Model Development & Forecasting
  • Build, train, and deploy time‑series forecasting models using techniques such as XGBoost, Random Forest, Linear regression–based models, ARIMA, SARIMA, Holt‑Winters, Prophet / FBProphet.
  • Operationalize model pipelines using Google Cloud Platform (GCP) services (BigQuery, Cloud Composer, Dataproc, Cloud Run) or equivalent cloud technologies (AWS, Azure).
  • Perform feature engineering, hyperparameter tuning, model validation, and continuous improvement of forecasting pipelines.
Data Engineering & Cloud Expertise
  • Develop scalable data processing workflows using Python, PySpark, and SQL.
  • Work with large datasets and cloud‑native data environments for analytics and modeling.
  • Collaborate with data engineering teams to ensure robust data pipelines and high‑quality training data.
Analytics & Anomaly Detection
  • Design and implement data anomaly detection systems to identify volume, pattern, and trend deviations.
  • Build automated alerting frameworks for early warning of data or forecast issues.
  • Investigate root causes of anomalies and recommend long‑term fixes.
Accuracy Metrics & Optimization
  • Develop and maintain accuracy measurement frameworks (e.g., MAPE, RMSE, MAE, WAPE, Bias).
  • Continuously fine‑tune and optimize model performance based on metric evaluations.
  • Communicate model accuracy trends and insights to both technical and business stakeholders.
Domain Expertise – Supply Chain & Demand Forecasting
  • Apply strong domain knowledge in retail supply chain, inventory planning, replenishment, and demand forecasting.
  • Partner with business teams to translate forecasting needs into data science solutions.
Required Qualifications
  • Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field.
  • 5+ years of experience as a Data Scientist with hands‑on model development.
  • Strong programming skills in Python, including PySpark and common data science libraries (Pandas, NumPy, SciPy, scikit learn).
  • Experience working with GCP or similar cloud platforms.
  • Hands‑on experience with time‑series forecasting, regression models, and ensemble methods.
  • Strong SQL experience and comfort with large‑scale datasets.
  • Ability to diagnose data issues, perform anomaly analysis, and build automated alerting solutions.
Preferred Qualifications
  • Experience in retail, supply chain, inventory, or demand forecasting systems.
  • Exposure to MLOps practices (CI/CD, model monitoring, retraining pipelines).

ROBOTICS TECHNOLOGIES LLC is an equal opportunity employer inclusive of female, minority, disability and veterans, (M/F/D/V). Hiring, promotion, transfer, compensation, benefits, discipline, termination and all other employment decisions are made without regard to race, color, religion, sex, sexual orientation, gender identity, age, disability, national origin, citizenship/immigration status, veteran status or any other protected status. ROBOTICS TECHNOLOGIES LLC will not make any posting or employment decision that does not comply with applicable laws relating to labor and employment, equal opportunity, employment eligibility requirements or related matters. Nor will ROBOTICS TECHNOLOGIES LLC require in a posting or otherwise U.S. citizenship or lawful permanent residency in the U.S. as a condition of employment except as necessary to comply with law, regulation, executive order, or federal, state, or local government contract

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