The Data Science team at AirAssess are working to develop and deploy AI and Machine Learning based solutions at scale.

The role requires that you have an extensive background in prototyping, modelling, model validation, production rollout at scale and post rollout improvements of machine learning based solutions. A proven track record in inventing and modifying advanced innovative algorithms and applying them to large data sets is essential.

You will have the flexibility to work from your own home.

Responsibilities

• Works independently or with small team to solve complex problems and create scalable models/algorithms that will be integrated into proprietary tools and products.
• Works directly with product senior leadership to translate their vision into practical solutions
• Effectively communicate what is being worked on, problems being solved, customer impact, and progress of projects
• Clearly communicate roadmap, backlog, and team updates across the organization
• Leads collaborative processes with cross-functional stakeholders to identify questions and complex business challenges and determine concrete plans of action in order to strategically define, design, and develop sophisticated machine learning models and algorithms to solve for each problem.
• Proactively identify and develop expertise in new technologies, methodologies, and techniques facilitating data science and systems engineering
• Identify predictive analytics opportunities to solve customer business problems and drive value
• Complete end-to-end execution of the data science This may be carried out in a collaborative environment but ranges from understanding business requirements, data discovery and extraction, model development and evaluation, to production pipeline implementation.

Required Skills and Experience:

• Masters, M.S or Ph.D. in a relevant technical field, or practical experience in a relevant discipline such as Computer Science, Physics, Engineering, Mathematics, or another relevant quantitative
• Overall 6-7+ years of experience in data science
• Exceptionally proficient with Artificial Intelligence/Machine Learning/Data Mining/Natural Language Processing/Pattern Recognition/Computer Vision.
• Strong understanding of statistical modelling and its application to solving business problems
• Strong experience in building at scale, production grade machine learning solutions and data pipelines.
• Highly proficient in languages and tools used in ML modeling like R, Python (SciKit Learn, SciPy, Numpy, etc.), Apache Spark (Scala or Python), H2O, Weka, TensorFlow, Torch, Keras.
• Extensive experience in building and rolling out scoring models, response models, optimization, forecasting, segmentation etc.
• Experience with cloud infrastructure and deployments is a plus
• Experience with horizontally scalable data stores such as Hadoop and other NoSQL technologies such as Map Reduce, Spark, HBase, etc., and associated schemas.
• Strong skills in data management approaches such as relational databases, data schemas, object stores, column stores, triple stores, graph stores, and/or document stores
• Ability to deliver accurate work products in a cross-functional matrix environment with product teams, engineering teams and business stakeholders.
• Excellent technical design, problem solving, debugging and communication skills

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