Sr. Data Scientist

Versa Networks•Santa Clara, CA

18d•$225,000 - $300,000•Hybrid

About The Position

We are seeking a talented and motivated Data Scientist to join our Machine Learning team. In this role, you will contribute to a wide range of data-driven projects, from exploratory data analysis to building and deploying machine learning models for a variety of Networking, Security and Language use-cases. You will work closely with cross-functional teams to uncover insights, solve complex problems, and drive data-informed decision-making.

Requirements

Masters degree in Computer Science/Engineering.
8+ years of experience in data science or a related field.
Strong proficiency in Python programming language.
Experience with data analysis and visualization tools (e.g., Pandas, NumPy, Matplotlib, Seaborn).
Knowledge of machine learning algorithms and techniques.
Familiarity with deep learning frameworks (e.g., TensorFlow, PyTorch).
Experience with natural language processing (NLP) and large language models (LLMs) is a plus.
Strong problem-solving and analytical skills.
Excellent communication and collaboration skills.
Applicants must be authorized to work in the US.

Nice To Haves

Experience with Go programming language.
Acceleration frameworks such as RAPIDS, Spark is preferable.
Knowledge of cloud platforms (e.g., AWS, GCP, Azure).
Experience with data version control and MLOps practices.

Responsibilities

Conduct exploratory data analysis (EDA) to understand data characteristics and identify patterns.
Utilize data visualization techniques to communicate insights effectively.
Ingest, clean, preprocess, and transform data to prepare it for analysis and modeling.
Handle missing values, outliers, and inconsistencies.
Labeling datasets appropriately for classification problems.
Build, train, and evaluate machine learning models, including traditional algorithms like CNNs, XGBoost, Transformers, Various Graph ML algorithms, Time Series modelling, LLM etc.
Collaborate with engineering teams to deploy models into production, ensuring scalability and reliability.
Be aware of and have experience in model quantization, model evaluation and various deployment formats like ONNX, GGUF etc.
Apply critical thinking and problem-solving skills to tackle complex data challenges.
Work effectively with data engineers, analysts, and domain experts to understand business requirements and translate them into actionable data insights.