Sr. Data Scientist - AWS

Position Summary:

We’re looking for a Data Scientist to join our analytics and AI team to design, build, and deploy machine learning and deep learning solutions for client engagements. You’ll work on end-to-end model development—data preparation, model design using PyTorch or TensorFlow, scaling with distributed engines like Spark, and production hand-off—while partnering with engineers, consultants, and business stakeholders

Responsibilities:

• Design, develop, and validate ML/DL models using PyTorch or TensorFlow for real-world business problems.
• Implement production-ready code in Python and collaborate with engineering teams to deploy models.
• Process and transform large datasets using distributed computing frameworks (e.g., Spark/PySpark).
• Lead model training, hyperparameter tuning, experiment tracking, and performance evaluation.
• Build reusable pipelines and components for feature engineering, training, and inference.
• Translate business use cases into technical solutions; present findings and model implications to non-technical stakeholders.
• Ensure model reliability, monitoring, and compliance with governance and security requirements.
• Mentor junior team members and contribute to best practices, code reviews, and architecture decisions.

Required Skills & Experience:

• 3–5 years of hands-on experience building ML or deep learning models using PyTorch or TensorFlow.
• Strong Python programming skills with clean, well-documented, version-controlled code.
• Experience working with distributed computing engines such as Spark for large-scale data processing.
• Solid grasp of core ML concepts: supervised/unsupervised learning, neural network architectures, regularization, evaluation metrics, and model validation.
• Practical experience with model training workflows, hyperparameter tuning tools, and ML tooling (e.g., MLflow, TensorBoard).
• Good communication skills and experience working in cross-functional teams.

Preferred qualifications (nice-to-have)

• Experience with graph databases and graph ML (e.g., Neo4j, Amazon Neptune).
  
• Experience in cybersecurity use cases (threat detection, anomaly detection, fraud analytics).
• Familiarity with PyTorch Geometric or other graph neural network libraries.
• Experience with cloud platforms (AWS, Azure, GCP) and containerization/orchestration (Docker, Kubernetes).
• Exposure to MLOps practices: CI/CD for models, monitoring, automated retraining.
• Advanced degree (MS/PhD) in Computer Science, Statistics, Data Science, or related field is a plus.

New Vision is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees