Flexible Text Analysis Jobs (NOW HIRING)

·       The Text and Speech Analyst is responsible for analyzing, interpreting, and evaluating language and text data to facilitate effective utilization across various contexts in support of our AI-powered solutions. This role examines written, spoken, and digital communications to identify patterns, trends, and opportunities related to language and speech to benefit our members in a cost-effective manner. 

·       The Text and Speech Analyst collaborates with cross-functional teams in the design, development, testing, and deployment of text and speech solutions that produce accurate, relevant, and high-quality outputs across various business applications. The ideal candidate will have a strong background in AI, natural language processing, and neural networks.

DEPARTMENTAL EXPECTATION OF EMPLOYEE 

·       Adheres to  Policy and Procedures and the  IPAAL Values and TRI Model  

·       Acts as a role model within and outside . 

·       Performs duties as workload necessitates.  

·       Maintains a positive and respectful attitude.  

·       Communicates regularly with the departmental leader about department issues.  

·       Demonstrates flexible and efficient time management and ability to prioritize workload.   

·       Consistently reports to work on time, prepared to perform duties of the position.  

·       Meets Department productivity standards. 

ESSENTIAL DUTIES AND RESPONSIBILITIES 

DESIGN AND OPTIMIZATION:

·       Design, develop, and refine automated speech recognition models and contextual text mapping techniques to ensure high-quality outputs for specific use cases.

·       Employ techniques to guide and enhance Automated Speech Response and text harvesting models, ensuring that the AI interactions are effective and efficient.

·       Develop effective AI text and speech services through proficient programming and utilization or ASR engines using standard and fit-for-purpose frameworks. 

·       Collaborate with cross-functional teams to ensure that the models are aligned with the business requirements and objectives.

·       Conduct testing of variants and analyzing model behaviors, including deviations and degradations within given frameworks.

·       Stay up to date with advancements in speech recognition and text harvesting technology and engineering best practices.

·       Collaborate with product managers, data scientists, ML engineers, and business stakeholders to integrate AI models into business processes, products, or workflows.

·       Create documentation and reusable libraries for internal and external use.

·       Partner with the MLOps Engineer and other stakeholders to establish and implement observability and monitoring frameworks to adequately and timely identify degradations and potential ethical/bias issues.

·       Establish and implement explainability frameworks.

·       Provide recommendations for improvement in the areas of AI acceptable use and ethics, collaborating with Legal and Compliance to ensure adherence.

AI GOVERNANCE AND SECURITY

·       Ensure data quality and integrity as they apply to text and speech models.

·       Ensure that data security protocols are followed in the definition and implementation of AI solutions in accordance with regulatory requirements and company policies.

·       Develop sety filters and guide the ethical use of prompts to prevent biased or harmful responses.

COLLABORATION AND STRATEGY

·       Work closely with IT, products, data engineers, data analysts, data scientists, and business stakeholders to understand needs, data requirements, and implement solutions.

·       Provide technical leadership and mentorship to junior data team members.

·       Provide training and support to team members on effective frameworks and best practices.

·       Stay updated on emerging technologies and best practices, making recommendations for continuous improvement.

ADDITIONAL DUTIES AND RESPONSIBILITIES 

·       Support model observability efforts to ensure adherence to company policies and enforce governance standards.

·       Other duties as assigned by manager or project needs

QUALIFICATIONS 

·       Bachelor’s or Master’s degree in Computer Science, Information Systems, Data Science, Linguistics, or a related field.

·       Minimum of 6 years of experience in NLP, LLMs, ASR engines and frameworks, data governance, data science, or a related role.

TECHNICAL SKILLS

·       Working knowledge of ASR engines using frameworks like Wav2vec or Deep Speech.

·       Working knowledge of Azure AI Services.

·       Advanced programming knowledge, including mastery of programming languages such as Python, C++, Java, and especially AI-centric libraries like TensorFlow, PyTorch, and Keras. 

·       Cloud computing and knowledge for deploying and managing AI applications on cloud platforms like AWS, Google Cloud, or Microsoft Azure. 

·       Expertise in classical speech processing methodologies like hidden Markov models (HMMs), Gaussian mixture models (GMMs), Artificial neural networks (ANNs), Language modeling, etc. 

·       Functional knowledge of Snowflake and/or Databricks for AI capabilities and data management.

·       Hands on experience on current deep learning (DL) techniques like Convolutional neural networks (CNNs), connectionist temporal classification (CTC) used for speech processing. 

·       Working knowledge of techniques for text parsing, sentiment analysis, and the use of transformers like GPT (generative pre-trained transformer) models.

·       Exposure to open-source models such as Kaldi or OpenAI Whisper.

·       Data management knowledge, including data pre-processing, augmentation, and generation of synthetic data, including the cleaning, labeling, and augmenting of data to train and improve AI models.

·       Proficiency in Transformer Models like BERT-base. ELMo, ULM-FIT.

·       Strong understanding of natural language processing concepts and techniques.

·       Working knowledge of cloud services (i.e., MS Azure, AWS, Google Cloud).

·       Experience with AI tools, such as MS Azure ML, Databricks AI, Snowflake CortexAI, Dataiku.

·       Strong knowledge of data governance, data security, and compliance practices.

·       Familiarity with data visualization and reporting tools (e.g., Webfocus, Power BI).

·       Hands on experience with MLOps processes.

SOFT SKILLS

·       Excellent analytical and problem-solving abilities.

·       Strong communication and interpersonal skills to collaborate with cross-functional teams.

·       Ability to lead projects and mentor junior stf.

·       Auto Insurance claims industry experience preferred.