Senior Data Scientist

What you will do: Build and ship core ML models for a speech-driven behavioral engine. Own end-to-end modeling from raw, long-form audio and layered annotations to production inference. Design audio features/embeddings, train and evaluate a suite of models, and deliver reproducible pipelines that meet accuracy, robustness, latency, and cost targets. Your skill set and experience: 5+ years building production ML systems, including 2+ years in speech/audio. Speech & signal processing: VAD, diarization, segmentation, denoising, spectral features (log-mel/MFCC), prosody (pitch/energy), long-form audio handling. SOTA audio models & embeddings: Wav2Vec2, HuBERT, wavLM (or similar); fine-tuning/self-supervised learning; contrastive/metric learning for downstream tasks. Data excellence: SQL, Python data stack (Pandas/Polars), ETL for audio+metadata, stratified sampling, leakage prevention, feature stores. ML Training: PyTorch, Hugging Face Transformers/Hub, mixed precision, hyperparameter tuning, transfer learning, cross-validation. Evaluation discipline: golden sets, robust speaker/content splits, ROC/PR/calibration, fairness/bias checks, ablations, drift/shift detection on embeddings and audio quality. MLOps, serving & reproducibility: FastAPI/gRPC around HF/torchaudio models, experiment tracking (W&B/MLflow), artifact/model versioning, CI/CD, observability, scalable batch/streaming inference. Proven ability to create and document novel IP (methods, architectures, or training/eval techniques) with clear prior-art awareness. Nice to have: Tooling: SpeechBrain, Lightning, OpenSMILE/Praat, Kaldi/Conformer/Emformer, Label Studio. Multimodal: ASR (e.g., Whisper) + paralinguistic features; emotion/prosody modeling; speaker embeddings (x-vectors, ECAPA-TDNN). Performance & deployment: quantization/distillation, Triton/CUDA basics, distributed training, real-time/streaming inference, on-device DSP (Rust/C++). Publications/patents/competition results demonstrating novel audio modeling work.

Full-time (40h/week), Remote  About Us We are a technology company on a mission to transform how organizations use data. We believe that for businesses to lead their industries, they must effectively harness their data. Our innovative, AI-powered analytics platform was built to make data-driven insights universally accessible, eliminating the need for complex infrastructure or large specialist teams. We empower non-technical users to connect to hundreds of data sources, ask questions in plain English, and get immediate, actionable insights. By unifying disparate data and enabling easy collaboration, we help businesses make faster, smarter decisions and turn their data into a pivotal competitive advantage. About the role We are seeking a Customer Success Engineer to handle customer-specific technical implementations and platform work. This is a crucial, forward-facing technical role designed to support our customers by addressing their unique account issues and technical needs, complementing our existing data team. This position will report directly to the CTO and work closely with internal stakeholders like the Product Manager and the Customer Success team. The primary focus will be on technical execution, with the potential for limited direct client communication via email or tickets. You will be instrumental in ensuring our customers are successfully onboarded and supported, directly impacting their success and our company's growth. Key responsibilities: Configure, debug, and manage ETL pipelines for new customer implementations. Build and maintain custom Airbyte connectors (Python or low-code/no-code) to meet specific customer data integration needs. Troubleshoot and resolve issues with Fivetran connectors. Provide AWS infrastructure support for customer environments, particularly managing S3 and IAM roles for secure data transfer Handle API integration work for customer accounts. Collaborate with and support our existing data team contractors. Utilize AI tools to debug SQL queries and troubleshoot various technical issues. Perform data quality assurance and validation to ensure data integrity. Set up customized BI dashboards for customer accounts within our platform. Review user LLM session logs to diagnose issues with our RAG pipeline and create detailed tickets for the engineering team. Requirements: Mid-level or higher engineering experience with a strong background in data engineering and ETL processes. Proficiency with Fivetran, Airbyte or equivalent ETL tools. Proficiency with AWS, specifically S3 and IAM roles. Solid experience with API integration, and debugging. Basic to advanced SQL proficiency for debugging and data validation. Proven ability to work independently and take ownership of customer-facing technical issues. Comfortable debugging issues throughout a data platform stack (from front-end to database and infrastructure) and writing clear, actionable bug tickets for the development team. Tools: Cloud: AWS (S3, IAM) Data Tools: Fivetran, Redshift, pgVector/Postgres, Metabase Languages: Ruby, Python Frontend: React (experience is helpful) Authentication: Keycloak AI: OpenAI, Anthropic Project Management: Trello Nice to have: Familiarity with AI/LLM tools and debugging (or enthusiasm to learn) Existing Airbyte/Fivetran/general ETL connector development experience Familiarity with data transformation tools and data modeling (eg. dbt) More advanced SQL and data analysis skills We would want at least 4 hours of overlap in the morning (9AM-1PM) as we have people in other timezones where the morning makes sense. Ideally would be US hours overlap (9AM-6PM or thereabouts) as reactive issues can come in from clients throughout the day.

About Us Is first AI-powered assistant for sustainability teams at consumer brands. We helps brands with tracing their supply chains, communicate their efforts to consumers, stay compliant with regulations like the EU Digital Product Passport, and stop wasting time on manual work. We’re pre-seed and working with early pilot brands. This is a ground-floor opportunity to join a fast-moving, mission-driven startup and help build a product with real-world impact. If you’re excited to co-build a mission-driven product from the ground up, shape real decisions, and earn meaningful ownership, this is the kind of experience that defines careers. About the Role You’ll work directly with the CEO to design and ship the first version of the product, integrate LLMs for automated workflows, and co-create a platform that helps sustainability teams actually move the needle. This role is ideal for someone who wants to have a positive impact in the world, work directly with really cool customers, build a product from scratch, and take full ownership over the technology and its direction. What You’ll Do Build and iterate on core platform and AI agent Own development across the stack: Lead architecture and backend decisions (Node, Postgres, Supabase) Supercharge our users’ interactions with the web (React) Unleash the power of AI for our customers (OpenAI, MCP, RAG) Evangelize agents coding tools like Cursor or Claude Code to multiply engineering impact Talk to users, gather feedback, and prototype quickly Lay the foundation for a high performing engineering organization ready to scale with the business, including culture, CI/CD, version control, and SDLC process Help shape product strategy and grow the engineering team What We’re Looking For 3+ years of full-stack development experience Strong background in modern full stack development. Our stack is DynamoDB, AWS, React, Redux, OpenAI, and Python (but this can be changed) Demonstrable experience with LLMs, agent frameworks, or workflow automation Excited about building something that drives impact in sustainability Comfortable working in ambiguity and iterating quickly, in a startup environment Clear communicator who’s proactive and self-directed Hungry to grow and ready to own a big piece of something early What You’ll Get A say in product, strategy, and company direction Experience building a real AI product in a high-impact industry A chance to work closely with brands that are shaping the future of sustainable fashion Room to lead, experiment, and make things happen