• Create and extend applied AI and ML solutions that enable intelligent, real-time decisions • Collaborate with engineering, product, and domain experts • Execute end-to-end data science tasks • Design, train, and evaluate machine learning and deep learning models • Apply techniques across computer vision, pattern recognition, predictive modeling, and generative AI • Translate ambiguous requirements into deployable systems • Build scalable data pipelines and feature engineering workflows • Partner with engineering to integrate models into production • Implement monitoring, validation, and retraining strategies • Use statistical methods to assess model quality

• Own end-to-end experimentation and analytical workflows that help the business learn fast and make confident decisions rooted in data. • Work closely with product, data engineering, and business stakeholders to start with customer and business goals, and work backwards to design the right experiments, features, metrics, and models. • Focus initially on optimizing our data pipeline for media data (audio and text) — helping improve throughput, quality, and utility of data as it flows through our systems. • Contribute to the evolution of our data infrastructure to support more advanced capabilities — including eventual creation of novel datasets and internal modeling workflows (e.g., for voice or multimodal data). • Design, analyze, and interpret experiments across tools/services/technologies to identify what works best — producing actionable insights that influence product direction, operations, and future research. • Translate complex analytical outcomes into clear business insights and product recommendations, occasionally contributing to broader thought leadership and research narratives.

• Translate ambiguous business problems into data science problems. • Analyze complex datasets to inform or make decisions. • Apply scientific principles and concepts to support significant invention. • Proactively identify opportunities and solutions to problems. • Create metrics and measurements to quantify the business impact of the work. • Write accurate and clear technical documentation and reports. • Communicate the approach and outcomes clearly with non-technical stakeholders. • Collaborate with stakeholders across a broad set of functions.

Role Description This role at Arbitration Forums is as unique as it is rewarding because of the AF IPAAL Values (Integrity, Passion, Accountability, Achievement, Leadership) and TRI Model (Trust, Respect, Inclusion). 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. 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 staff. - Auto Insurance claims industry experience preferred. Requirements - Adheres to AF Policy and Procedures and the AF IPAAL Values and TRI Model. - Acts as a role model within and outside AF. - 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. Benefits - Support model observability efforts to ensure adherence to company policies and enforce governance standards. - Other duties as assigned by manager or project needs. Company Description This is a fully remote position requiring reliable high-speed internet access and a dedicated workspace. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.