Data Scientist/Machine Learning Scientist

Aptonet; Atlanta (GA); Hybrid; USD 110,000 - 170,000; Full time

Job summary

Aptonet is seeking a data science professional to define and solve complex business problems using statistical analysis and machine learning in a hybrid Atlanta-based team.

You will design, develop, implement, and monitor models through their lifecycle, collaborating with business and technical teams to identify analytics use cases and process improvements. Strong knowledge of ML techniques and big-data tools is required, with excellent communication skills.

Qualifications

• Strong knowledge of ML techniques such as Random Forest, Gradient Boosting, XGBoost, SVM, deep learning, K-means, and DBSCAN.
• Advanced proficiency with SQL and Python or Scala.
• Experience with big-data technologies such as PySpark and SparkR.
• Strong analytical, written, and verbal communication skills.

Responsibilities

• Define and solve complex business problems using statistical analysis and machine learning.
• Design, develop, implement, and monitor models throughout their lifecycle.
• Collaborate with business and technical teams to identify process improvements and analytics use cases.
• Evaluate the accuracy and quality of data sources and models.
• Communicate findings and recommendations effectively to technical and nontechnical stakeholders.
• Stay current with emerging machine learning models, tools, and technologies.

Skills

Machine learning techniques

SQL

Python/Scala

Communication skills

Education

Bachelor's/Master's/PhD in CS/EE/ML/Statistics or related field

Tools

PySpark

SparkR

Job description

The centralized AI and Data Science team partners with product teams across the organization to identify high-impact business challenges and develop advanced analytics and machine learning solutions.

Key Responsibilities:

• Define and solve complex business problems using statistical analysis and machine learning.
• Design, develop, implement, and monitor models throughout their lifecycle.
• Collaborate with business and technical teams to identify process improvements and analytics use cases.
• Evaluate the accuracy and quality of data sources and models.
• Communicate findings and recommendations effectively to technical and nontechnical stakeholders.
• Stay current with emerging machine learning models, tools, and technologies.

Required Experience:

• Strong knowledge of machine learning techniques such as Random Forest, Gradient Boosting, XGBoost, Support Vector Machines, deep learning, K-means, and DBSCAN.
• Advanced proficiency with SQL and Python or Scala.
• Experience with big-data technologies such as PySpark and SparkR.
• Strong analytical, written, and verbal communication skills.
• Bachelor's, master's, or Ph.D. in Computer Science, Electrical Engineering, Machine Learning, Statistics, or a related field.

Work Arrangement:

• Candidates in the Atlanta area: Hybrid, with two days per week in the office.
• Candidates outside the Atlanta area: Fully remote