Data Scientist

Quantum Technologies. LLC; Nashville (TN); Presencial; USD 120.000 - 180.000; Jornada completa

Descripción de la vacante

Quantum Technologies, LLC in Nashville seeks a Senior Data Scientist to design and deploy cloud-based forecasting pipelines. You will build time-series models, perform feature engineering, and operationalize predictions at scale using GCP or equivalent platforms.

The role emphasizes anomaly detection, alerting, and collaboration with data engineering and business stakeholders to improve model accuracy with metrics like MAPE, RMSE, and MAE.

Formación

• 5+ years of hands-on data science experience.
• Strong Python and PySpark proficiency.
• Experience with cloud platforms (GCP/AWS/Azure) and time-series forecasting.
• Ability to diagnose data issues and build alerting systems.

Responsabilidades

• Build, train, and deploy time-series forecasting models.
• Operationalize model pipelines using cloud services.
• Develop scalable data processing workflows.
• Design anomaly detection and alerting systems.
• Measure model accuracy and optimize performance.

Conocimientos

Python

PySpark

Time-series

SQL

ML models

Model deployment

Educación

Bachelor's or Master's degree in Data Science, CS, Statistics, Mathematics, or related field

Herramientas

BigQuery

Cloud Composer

Dataproc

Cloud Run

Descripción del empleo

Banking & Finance,Utilities/ Energy,Telecom,Aerospace/ Airlines,IT/Software,Media/ Entertainment

Work Authorization:

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

• Battery'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).

We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.