Lead Data Scientist (PhD) Intelligent Forecast

Overview

Hybrid
$95+
Contract - W2
Contract - 12 Month(s)
Able to Provide Sponsorship

Skills

A/B Testing
Advanced Analytics
Agile
Amazon S3
Amazon Web Services
Apache Spark
Artificial Intelligence
Automotive Manufacturing
Big Data
Cloud Computing
Computer Science
Data Engineering
Data Science
Databricks
Deep Learning
Design Architecture
DevOps
Docker
Google Cloud Platform
IP
Innovation
Kubernetes
Continuous Integration
Machine Learning Operations (ML Ops)
Microsoft Azure
NumPy
Python
Snow Flake Schema
Statistical Models
SQL
Supply Chain Management
Time Series
Telematics
TensorFlow
PyTorch
XGBoost
scikit-learn
Workflow

Job Details

Title: Lead Data Scientist (PhD) Intelligent Forecast
Location: Plano, TX (Onsite/Hybrid if applicable)
Rate: $95/hr

Job Description:

We are seeking a Lead Data Scientist with a PhD and a deep understanding of forecasting and AI/ML methodologies to lead the design, development, and deployment of an enterprise-grade Intelligent Forecasting Application for a global automotive OEM. This is a high-visibility, high-impact role in Plano, TX, ideal for someone with a strong background in advanced analytics, machine learning, MLOps, and automotive/manufacturing environments.

Key Responsibilities:
  • Lead the end-to-end design, architecture, and delivery of the Intelligent Forecast Application.

  • Translate complex automotive business problems into scalable AI/ML solutions.

  • Design and implement advanced models using ARIMA, LSTM, GRU, Transformers, XGBoost, Bayesian models, and other modern techniques.

  • Integrate external and internal data sources, including market trends, production data, economic indicators, and unstructured data.

  • Develop MLOps pipelines for model versioning, deployment, monitoring, and retraining.

  • Collaborate with cross-functional teams (Sales, Marketing, Supply Chain, Manufacturing, etc.).

  • Evaluate model performance with metrics like RMSE, MAPE, Pinball Loss, and conduct A/B testing.

  • Mentor junior data scientists and contribute to a culture of innovation and research.

  • Present findings internally and externally, contributing to IP development.

Required Qualifications:
  • PhD in Data Science, Computer Science, Statistics, Applied Mathematics, Operations Research, or a related field.

  • 5+ years of experience as a Data Scientist/ML Engineer delivering production-level forecasting solutions.

  • Automotive or complex manufacturing domain experience is required.

  • Expertise in Python (NumPy, Pandas, Scikit-learn, Statsmodels), SQL, and tools like TensorFlow, PyTorch, Prophet, MLflow, Snowflake, Databricks, etc.

  • Experience with cloud platforms (AWS, Azure, or Google Cloud Platform).

  • Solid grasp of data engineering, feature engineering, and big data ecosystems (Spark, S3, ADLS).

  • Hands-on MLOps experience with Docker, Kubernetes, CI/CD.

  • Strong background in statistical modeling, time series forecasting, and deep learning for sequential data.

  • Excellent communication and problem-solving skills, with the ability to influence stakeholders.

Preferred Qualifications:
  • Publications in forecasting/time series/machine learning conferences or journals.

  • Experience with real-time forecasting systems, streaming analytics, and automotive data (telematics, sensor, dealership).

  • Familiarity with Agile, Git, and modern DevOps workflows.

Soft Skills:
  • Strong collaboration and mentorship abilities.

  • Strategic mindset with a passion for innovation and continuous learning.

  • Ability to thrive in a dynamic, high-impact, fast-paced environment.

This role offers an exceptional opportunity to lead strategic AI-driven forecasting initiatives in one of the most innovative automotive settings. Apply now to shape the future of intelligent automotive planning and production.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

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