Machine Learning Engineer
Python
Advanced Analytics
Ai Ml
Analytics
Artificial Intelligence
Big Data
Cloud Platform
Cloud Platforms
Data & Ai
Data Analysis
Data Analytics
Data Architecture
Data Integration
Data Mining
Data Pipeline
Data Platform
Data Processing
Data Science
Database
Databases
Databricks
Deep Learning
Detection Engineering
ETL
Feature Engineering
Fraud Analytics
Machine Learning
Machine Learning Engineer
Predictive Analytics
Predictive Modeling
Production Analytics
Statistical Modeling
Job Description
Photon is seeking a seasoned Machine Learning Engineer to design and deploy analytics-driven models that solve real business problems. The role is based in New Jersey with onsite collaboration, and you will partner with product and engineering teams to deliver end-to-end ML solutions, deploy models into production, and leverage Python, Spark, and Databricks to generate actionable insights.
Responsibilities
- Analyze use cases and design analytics models using statistical and machine learning methods tailored to specific business needs.
- Develop machine learning algorithms aimed at personalizing customer experiences and extracting actionable business insights.
- Apply data mining and machine learning techniques across forecasting, prediction, segmentation, recommendation, and fraud detection.
- Augment company data by integrating third-party data sources to enhance analytics capabilities.
- Improve data collection processes to capture information essential for analytics systems.
- Prepare raw data for analysis, including cleaning, imputing missing values, and standardizing formats using Python libraries such as Pandas and NumPy.
- Implement scalable machine learning models with attention to performance, using tools like PySpark in Databricks.
- Design and build infrastructure that supports large-scale data analytics and experimentation.
- Utilize Jupyter Notebooks for data exploration and model development.
Requirements
- A bachelor’s or master’s degree in Computer Science, Mathematics, Physics, or related fields; a PhD is preferred but not required.
- Minimum of 5 years of experience in data analytics, with a solid grasp of core statistical algorithms including classification and regression.
- Strong experience with Python-based machine learning libraries such as scikit-learn, TensorFlow, and PyTorch.
- Proficiency with analytics platforms like Databricks for large-scale data processing.
- At least 4 continuous years of experience with Spark, particularly using PySpark.
- Hands-on experience with data processing and analysis tools such as Pandas, NumPy, and Jupyter Notebooks.
Technologies
- Python
- Spark
- Databricks
- Pandas
- NumPy
- Jupyter Notebooks
- PySpark
- scikit-learn
- TensorFlow
- PyTorch
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