Overview
On Site
$140,000 - $160,000
Full Time
Skills
Algorithms
Amazon S3
Amazon Web Services
Analytical Skill
Apache Hadoop
Apache Spark
Applied Mathematics
Big Data
Cloud Computing
Computer Science
Conflict Resolution
Continuous Delivery
Continuous Integration
Dashboard
Data Science
Data Storage
Data Visualization
Data Warehouse
Databricks
Decision-making
Deep Learning
Demand Planning
Design Of Experiments
Distributed Computing
Docker
FOCUS
Forecasting
Good Clinical Practice
Google Cloud Platform
Inventory Optimization
Keras
Kubernetes
Machine Learning (ML)
Machine Learning Operations (ML Ops)
Pandas
Problem Solving
Production Scheduling
PyTorch
Python
SQL
Snow Flake Schema
Statistical Models
Statistics
Supply Chain Management
Tableau
TensorFlow
Time Series
scikit-learn
Manufacturing
Microsoft Azure
Microsoft Power BI
NumPy
Operations Research
Job Details
Required Qualifications:
- Education: MUST HAVE PhD in Data Science, Computer Science, Statistics, Applied Mathematics, Operations Research, or a closely related quantitative field.
- Experience: years of hands-on experience in a Data Scientist with a significant focus on developing and deploying advanced forecasting solutions in a production environment.
- MUST HAVE AUTOMOBILE DOMAIN EXPERIENCE
- Demonstrated experience designing and developing intelligent applications, not just isolated models.
- Experience in the automotive industry or a similar complex manufacturing/supply chain environment is highly desirable.
- Technical Skills Expert proficiency in Python (Numpy, Pandas, Scikit-learn, Statsmodels) and/or R. Strong proficiency in SQL.
- Machine Learning/Deep Learning Frameworks: Extensive experience with TensorFlow, PyTorch, Keras, or similar deep learning libraries.
- Forecasting Specific Libraries: Proficiency with forecasting libraries like Prophet, Statsmodels, or specialized time series packages.
- Data Warehousing & Big Data Technologies: Experience with distributed computing frameworks (e.g., Apache Spark, Hadoop) and data storage solutions (e.g., Snowflake, Databricks, S3, ADLS).
- Cloud Platforms: Hands-on experience with at least one major cloud provider (Azure, AWS, Google Cloud Platform) for data science and ML deployments.
- MLOps: Understanding and practical experience with MLOps tools and practices (e.g., MLflow, Kubeflow, Docker, Kubernetes, CI/CD pipelines).
- Data Visualization: Proficiency with tools like Tableau, Power BI, or similar for creating compelling data stories and dashboards.
- Analytical Prowess: Deep understanding of statistical inference, experimental design, causal inference, and the mathematical foundations of machine learning algorithms.
- Problem Solving: Proven ability to analyze complex, ambiguous problems, break them down into manageable components, and devise innovative solutions.
We are seeking an exceptional and highly motivated Lead Data Scientist with a PhD in Data Science, Computer Science, Applied Mathematics, Statistics, or a closely related quantitative field, to spearhead the design, development, and deployment of an automotive OEM s next-generation Intelligent Forecast Application will leverage cutting-edge machine learning, deep learning, and statistical modeling techniques to build a robust, scalable, and accurate forecasting system crucial for strategic decision-making across the automotive value chain, including demand planning, production scheduling, inventory optimization, predictive maintenance, and new product introduction
Regards,
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