Description

You will develop and test complex analytical models to solve business problems using structured and unstructured data.

Responsibilities

• Code and test customized analytical models of medium to high complexity.
• Implement best practices for writing, testing, and modularizing analytic functionality.
• Select appropriate modeling techniques based on data limitations and business requirements.
• Build and implement machine learning workflows, including model governance and monitoring.
• Construct GUI interfaces and manage the full data science project life cycle.

Required Skills

• 5+ years of experience in data science roles.
• Extensive experience with Python, R, and SQL.
• Proficiency in Python packages including NumPy, SciPy, and SciKit-learn.
• Hands-on experience with Deep Learning frameworks: TensorFlow, Keras, and PyTorch.
• Proven experience with Regression, Decision trees, Bayesian networks, Random Forest, Logistic regression, Support vector machine, Gradient boosting, Clustering, and Dimensionality Reduction algorithms.
• Experience building and implementing Time series and forecasting models.
• Operational knowledge of Elasticsearch.
• Experience with version control systems such as Git, GitHub, or Subversion/SVN.
• Ability to gather, interpret, and manipulate complex datasets.

Preferred Skills

• Natural Language Processing and text analytics using NLTK or SpaCy.
• Experience with Data Science platforms like Dataiku, H2O, or Azure.
• Cloud platform experience with AWS, Azure, or GCP.
• Knowledge of Big Data technologies including Hadoop, Hive/HQL, HDFS, Spark/PySpark, or Kafka.
• Experience working in an Agile environment.

Key Skills

Education

Any Graduate