Data Scientist

Valiant Technologies LLC; Nashville (TN); On-site; USD 150,000 - 190,000; Full time

Job summary

Valiant Technologies LLC is seeking a Senior Data Scientist with deep experience in cloud-based data platforms and time-series forecasting. You will develop, train, and operationalize predictive models at scale, leveraging Python, PySpark, and GCP services such as BigQuery and Cloud Composer.

You will identify data anomalies, build alerting frameworks, and continuously improve model accuracy through robust evaluation metrics, collaborating with supply chain teams to translate forecasting needs

Qualifications

• 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.
• Experience 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.

Responsibilities

• Build, train, and deploy time-series forecasting models at scale.
• Operationalize model pipelines using cloud services and maintainability.
• Develop scalable data processing workflows using Python and PySpark.
• Design data anomaly detection systems and automated alerting.
• Develop accuracy metrics and continuously tune model performance.

Skills

Python

PySpark

Time-series forecasting

Model deployment

Pandas

NumPy

SciPy

scikit-learn

SQL

GCP

Education

Master's degree in Data Science

Tools

BigQuery

Cloud Composer

Dataproc

Cloud Run

Airflow

Job description

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.