Senior Data Scientist

Develop and optimize machine learning models for classification, regression, clustering, and recommendation systems.

Implement deep learning architectures using frameworks like TensorFlow, PyTorch, or Keras.

Preprocess and analyze large datasets to extract meaningful insights.

Fine-tune models for performance, accuracy, and efficiency.

Deploy ML models into production environments using cloud platforms (AWS, Azure, GCP) or edge devices.

Collaborate with data engineers to build robust data pipelines.

Conduct research on emerging AI/ML technologies and apply them to real-world problems.

Perform model evaluation, A/B testing, and error analysis to improve performance.

Work with stakeholders to understand business requirements and translate them into AI solutions.

Requirements:

• 2-4 years of experience in AI/ML development.
• Proficiency in Python and ML libraries such as TensorFlow, PyTorch, or Keras.
• Strong understanding of Machine Learning algorithms, deep learning architectures, and statistical modeling.
• Experience with data preprocessing, feature engineering, and model optimization.
• Familiarity with big data technologies (Spark, Hadoop) and databases (SQL, NoSQL).
• Understanding of NLP, computer vision, or reinforcement learning is a plus.

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  Ability to work both independently and collaboratively in a fast-paced, agile environment.
• You have an eye for detail, esp. around user experience and secure coding practices.
• A strong drive to learn and explore.

The Ideal Candidate:

• Is by nature highly team-oriented and collaborative. Believes the best work can be achieved when a talented group of smart people work effectively together.
• Has proper understanding of semantic markup and knows how to build interactive pieces that comply with web accessibility standards.
• Has personal projects or frontend related code contributions to open-source community and actively publishes on web development related development topics