Data Science and Machine Learning Consultant

Responsibilities

• Develop and debug in Python, Java, C or C++. Proficient in git version control. R and Matlab are also relevant.
• Design and evaluate intrinsic and extrinsic metrics of your model?s performance which are aligned with business goals.
• Define how we build and deploy systems around intelligent algorithms.
• Work computational packages (TensorFlow, Theano, PyTorch, Keras, Scikit-Learn, NumPy, SciPy, Pandas, Pickle, Seaborn, statsmodels, NLTK).
• Use Natural Language Processing for Name Entity Recognition, Sentiment Analysis and topic modeling. Familiarity with Latent Dirichlet Allocation.

Required Skills

• Expert familiarity with of a variety of classic and modern machine learning techniques including deep learning, clustering, decision tree, classification, regression and neural networks.
• Knowledge of mining complex data (including structure and unstructured), identifying patterns, and feature engineering.
• Knowledge of data engineering and experience with big data
• Linux and shell scripting expertise.
• Proficiency with SQL and NoSQL databases.
• Proficiency with scalable data extraction tools (e.g. Cassandra, MongoDB).
• Proficiency with Python, R, Scala, Spark, Java and/or SAS.

Required Experience

• At least 6 years of Hands on Experience in Microsoft Azure Cloud DW with Databricks, AI/ML, Azure ML, Snowflake experience.
• Experience with design patterns and implementation and deployment AI and/or data science products.
• Experienced with deploying and managing infrastructures based on Docker, Kubernetes, or OpenStack, and Clouds such as OpenShift, Azure, AWS or Google Cloud Platform.
• Experience developing, testing and deploying APIs.
• Experience building applications based on Microservices Architecture.
• Experience with Spring Framework: Core, Integration, MVC and SpringBoot.

Education Requirements

• Bachelor’s Degree in Computer Science, Computer Engineering or a closely related field