Description

You will design, build, and maintain machine learning models to solve complex business problems. You will lead projects from initiation to completion, focusing on automated deployment and optimized performance.

Responsibilities

• Perform data cleansing, merging, enrichment, and feature engineering to prepare datasets for modeling.
• Build stochastic and machine learning algorithms to address specific business requirements.
• Maintain and optimize deep learning models, ensuring seamless deployment across Dev, QA, and Prod environments.
• Collaborate with data engineers to containerize models and build deployment pipelines using MLOps workflows.
• Design, prototype, and maintain APIs for consuming machine learning models at scale.

Required Skills

• 3 to 7 years of experience in data science and machine learning.
• Proficiency in Python programming.
• In-depth modeling experience with supervised, unsupervised, and deep learning models (CNN, RNN, LSTM, BERT, Transformers).
• Hands-on experience with PyTorch, Scikit-Learn, TensorFlow, or SparkML.
• Experience with data wrangling, cleaning, preparation, and dimensionality reduction.
• Knowledge of vector algebra, statistical modeling, and probabilistic modeling.
• Strong understanding of advanced statistical techniques, including regression and statistical tests.
• Familiarity with SQL or NoSQL databases.
• Ability to design and maintain data architectures and pipelines.

Preferred Skills

• Experience with ML deployment frameworks such as Azure ML Studio or AWS SageMaker.

Key Skills

Education

ANY GRADUATE