Description

You will design and implement machine learning models and graph-based analytical systems.

Responsibilities

• Develop and operationalize data pipelines to assimilate large datasets from multiple databases.
• Execute graph analytics, graph-based learning, and graph representation tasks.
• Apply machine learning methods and statistical models to create actionable outcomes.
• Build and maintain analytical and computationally intensive software systems.
• Document quantitative analysis and adhere to standardized project methodologies.

Required Skills

• 10+ years of professional experience in software development and machine learning.
• Bachelor's degree in Computer Science, Physical Sciences, Econometrics, Statistics, or a quantitative discipline.
• Proficiency in Python, R, or Scala.
• Hands-on experience with ML packages including Pandas, Scikit-Learn, XGBoost, Catboost, LightGBM, AutoML, Optuna, and Hyperopt.
• Expertise in Graph Learning using NetworkX, Torch-Geometric, Graphframes, or Graphistry.
• Knowledge of algorithms such as Graph Neural Networks (GAT), Page Rank, Centrality Analysis, and Louvain/Hierarchical Clustering.
• Experience with Graph Databases such as TigerGraph or Neo4j and query languages like Cypher or Hive.
• Experience with cloud technologies including AWS, GCP, Azure, or Databricks.
• Familiarity with visualization tools like Matplotlib, Seaborn, and Geopandas.

Preferred Skills

• Experience with Zero Shot/Few Shot learning and Outlier Detection methods.

Key Skills

Education

Bachelor's Degree