• Build, maintain, and improve Quick Suite dashboards, analyses, datasets, and Paginated Reports for aviation KPIs (revenue, fleet utilization, delays, crew duty, etc.). • Use SQL to query and validate data from our Redshift layer and underlying PostgreSQL sources. • Perform data cleaning, outlier detection, and light transformation. • Create and manage QuickSight namespaces, users, folders, permissions, and Row-Level Security rules. • Own parts of the ETL pipeline: monitor refreshes, debug failures, and help prepare for incremental / future Spark-based processing. • Segment and prepare data to support operator-isolated dashboards and targeted reports. • Identify, investigate, and resolve data quality issues and discrepancies (e.g., duplicate records, freshness alerts). • Add and test new calculated fields and data sources to meet evolving reporting needs. • Communicate insights clearly through visualizations, annotated screenshots, and concise one-pagers to sales, product, and management teams. • Collaborate with the Product Owner and management to translate business requirements into practical BI deliverables.

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description We are looking for a Data Scientist to help design, build, and deploy machine learning and generative AI solutions that power real world products and decisions. In this role, you’ll work on production AI systems, partner closely with engineering and product teams, and take ownership of meaningful data science initiatives from idea to deployment. This is a hands-on, individual contributor role for someone who enjoys shipping models, working with modern AI tooling, and solving real business problems with data. Responsibilities - Machine Learning & Data Science - Develop, evaluate, and deploy predictive and generative models for real production use cases - Perform feature engineering and data preparation for modeling workflows - Translate business and product questions into analytical solutions - Generative AI - Build and maintain LLM powered features and services - Develop retrieval augmented generation (RAG) pipelines using embeddings and vector databases - Integrate LLMs with APIs and internal tools using structured function calling - Finetune foundation models with parameter efficient approaches (e.g., LoRA) - Evaluate model quality, detect hallucinations, and implement safety guardrails - Use synthetic data to improve model performance, testing, and fairness - Optimize inference performance and cost across different model providers - MLOps & Production Systems - Deploy and operate machine learning and GenAI models in production - Build CI/CD pipelines for models and data workflows - Monitor performance, data quality, and model drift - Design versioning, rollback, and retraining strategies - Partner with platform and infrastructure teams to ensure reliability and scalability - RealTime Analytics - Build low latency data pipelines and real time decisioning systems - Work with streaming data and event driven architectures - Support systems with strict uptime and response time requirements - Contribute to feature stores used for both real time and batch inference Qualifications - 3–6 years of experience in data science, machine learning, or applied AI - A degree (Master's or better preferred) in Computer Science, Data Science or related fields - KNOWLEDGE/SKILLS/ABILITIES - Strong Python and SQL skills - Hands-on experience deploying models into production - Familiarity with cloud platforms (AWS, Azure, or GCP) - Experience with modern ML frameworks (PyTorch, TensorFlow, scikit-learn) - Exposure to LLMs, embeddings, and GenAI workflows - Ability to communicate clearly with engineers, product managers, and non-technical partners - Nice to Have - Experience with streaming data systems - Experience operating models at scale - Knowledge of MLOps tools and observability practices - Experience building AI solutions that support customer facing products Physical Demands and Working Conditions While performing the duties of this job, the employee is occasionally required to stand; walk; sit; use hands to finger, handle or feel objects, tools or controls; reach with hands and arms; climb stairs; talk or hear. The employee must have the ability to operate a personal computer and express or exchange ideas by means of the spoken word. May be required to sit and/or stand for long periods of time. Specific vision abilities required by this job include close vision, distance vision, color vision, peripheral vision, depth perception, and ability to adjust focus. May be required to lift or move 10+ pounds. Pay Range USD $116,400.00 - USD $198,200.00 /Yr.

• Write production code in Python. • Design, launch, and analyze experiments to optimize ad campaigns. • Create reporting and analytics tools for the Data Science Team's customers. • Translate insights from reporting tools into tvScientific's Data Science Product.

• Build key relationships with stakeholders across product, engineering, finance, and operations • Use decision-modeling frameworks to assess potential outcomes and guide decision-making • Collaborate in a small, agile team to produce outsized business impact • Identify unaddressed problems and offer improved solutions • Build tools and dashboards for data-driven decision-making