Data Scientist

Ethereum Technologies; Nashville (TN); On-site; USD 140,000 - 190,000; Full time

Job summary

Ethereum Technologies is seeking a Senior Data Scientist with deep expertise in cloud-based data platforms (GCP or similar), Python/PySpark, and advanced time-series forecasting. You will lead model development for demand forecasting, build scalable pipelines, and operationalize ML models across cloud environments.

Ideal candidates bring 5+ years in data science, strong SQL, and hands-on experience with forecasting methods and anomaly detection.

Qualifications

• Bachelor's or Master's degree in data science, computer science, statistics, mathematics, or related field.
• 5+ years in data science with hands-on model development and deployment.
• Strong Python, PySpark, and data science libraries experience.
• Experience with GCP or similar cloud platforms and time-series forecasting.

Responsibilities

• Build, train, and deploy time-series forecasting models using XGBoost, ARIMA, Prophet, and related methods.
• Operationalize model pipelines on cloud platforms (GCP/AWS/Azure).
• Develop scalable data processing workflows with Python, PySpark, and SQL.
• Design anomaly detection systems and automated alerting for forecast issues.
• Maintain accuracy metrics and communicate trends to stakeholders with domain insight in supply chain.

Skills

Python

PySpark

Time-series forecasting

SQL

GCP experience

Model deployment

Domain knowledge - supply chain

Data engineering

Education

Bachelor's or Master's in Data Science/CS/Statistics

Tools

BigQuery

Cloud Composer

Dataproc

Job description

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

Client:

To Be Discussed Later

Employment Type:

W-2, 1099, C2C

Work Authorization:

US Citizen, Green Card, H-1B, OPT-EAD, CPT, Other

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).

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.