Language Researcher

Key Skills

Python Programming, Scala Programming, C++, Java Programming, Machine learning techniques, Data science techniques, SQL, Apache Hadoop, MapReduce, TensorFlow, PyTorch, R Programming

Job Description

Tiger Analytics is looking for experienced Data Scientists to join our fast-growing advanced analytics consulting firm. Our employees bring deep expertise in Data Science, Machine Learning and AI. We are the trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner. We are looking for top-notch talent as we continue to build the best global analytics consulting team in the world.

Are you interested in solving natural language problems that involve speech and text utterances from millions of customers and hundreds of thousands of video content? Do you have experience in building large-scale speech, NLP and machine learning systems? Do you want to conduct industry-leading applied research to create voice assistants to help millions of households interact with video and music content on their TV, PC, Phone, and Mobile devices as well as troubleshoot problems without human intervention?

As a Language Researcher, you would collaborate with engineers, researchers and editorial teams to help design linguistic annotations, ontologies, taxonomies and/or semantic schemas. Your daily work will involve working closely with product managers to understand business requirements and to help build more effective NLP systems.

Key Responsibilities

• Collaborate with business partners to develop innovative solutions to meet objectives utilizing cutting edge techniques and tools.
• Effectively communicate the analytics approach and how it will meet and address objectives to business partners.
• Advocate and educate on the value of data-driven decision making; focus on the “how and why” of solutioning.
• Lead analytic approaches; integrate solutions collaboratively into applications and tools with data engineers, business leads, analysts and developers.
• Create repeatable, interpretable, dynamic and scalable models that are seamlessly incorporated into analytic data products.
• Develop grammars for NLP systems in different languages and/or define and implement higher level grammar architecture.
• Collaborate with engineers and researchers to develop coherent and comprehensive meaning representation frameworks, considering quality, fairness and machine bias.
• Train and/or evaluate NLP or dialogue systems, identify errors/regressions and propose solutions.
• Guide annotation efforts to train and test new capabilities.
• Measure and analyze accuracy and throughput of annotated data.
• Use data science and machine learning methods to bootstrap new functionalities.
• Handle competing requests from a range of data customers.
• Tackle complex problems that arise in production and find customer-centric solutions.
• Engineer features by using your business acumen to find new ways to combine disparate internal and external data sources.
• Share your passion for Data Science with the broader enterprise community; identify and develop long-term processes, frameworks, tools, methods and standards.
• Collaborate, coach, and learn with a growing team of experienced Data Scientists.
• Stay connected with external sources of ideas through conferences and community engagements.

Requirements

• Bachelors Degree in Data Science, Computer Science, or a degree in Linguistics or Computational Linguistics with knowledge of semantics, syntax, morphology and/or discourse.
• 4+ years of Data Science and Machine Learning experience required.
• Proficiency in Python or R. Ability to write complex SQL queries
• Proficiency with Machine Learning concepts and modeling techniques to solve problems such as clustering, classification, regression, anomaly detection, simulation and optimization problems on large scale data sets.
• Experience with AWS is a plus.
• Ability to implement ML best practices for the entire Data Science lifecycle.
• Ability to apply various analytical models to business use cases (NLP, Supervised, Un-Supervised, Neural Nets, etc.)
• Exceptional communication and collaboration skills to understand business partner needs and deliver solutions.
• Bias for action, with the ability to deliver outstanding results through task prioritization and time management.
• Experience with data visualization tools — Tableau, Power BI, etc. preferred.
• Knowledge on experimental design, evaluation methodologies, qualitative and quantitative analysis.
• Independent and driven person who enjoys working in a fast-paced and collaborative team environment.