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 seeks a skilled Machine Learning Engineer for an onsite role in New Jersey. The position focuses on designing and deploying analytics models through statistical and machine learning approaches, collaborating with product and engineering teams to solve complex business problems, and delivering end-to-end ML solutions in production using Python, Spark, and Databricks.
Responsibilities
- Assess business use cases and design analytics models using statistical and machine learning methods tailored to specific requirements.
- Develop machine learning algorithms to personalize customer experiences and generate actionable business insights.
- Apply data mining and ML techniques, including forecasting, prediction, segmentation, recommendation, and fraud detection.
- Augment company data with third-party sources to broaden 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 data frameworks (Pandas, NumPy).
- Implement ML models with attention to performance and scalability using PySpark in Databricks.
- Design and build infrastructure to support large-scale data analytics and experimentation.
- Utilize tools such as Jupyter Notebooks for data exploration and model development.
Requirements
- Bachelor's or graduate degree in Computer Science, Mathematics, Physics, or related fields; PhD preferred but not required.
- Minimum five years of experience in data analytics with a strong understanding 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 four years of continuous experience with Spark, particularly PySpark.
- Hands-on experience with data processing and analysis tools including Pandas, NumPy, and Jupyter Notebooks.
Technologies
- Python
- Spark
- Databricks
- Pandas
- NumPy
- Jupyter Notebooks
- PySpark
- scikit-learn
- TensorFlow
- PyTorch
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