Applied Data Scientist Contract

Were looking for an authentic collaborative and accountableApplied Data Scientistto join the Arcurve AREPassionate about technologyAn authentic and creative humanDriven to succeedA believer in the importance of teamworkCommunity-mindedAn expert problem solverSomeone who thrives on challengeMotivated by exceptional resultsSomeone who cares about your clientsTHE GOALTo deliver best-in-class technical solutions across a broad array of clients in different industries utilizing the tech stack best suited to solving the problem with a focus on delivering business value for our ROLEArcurve delivers applied machine learning for clients operating in complex technical environments. Our project portfolio spans computer vision timeseries forecasting causal analysis and large language model and agentic a Data Scientist you will own the analytical approach on client engagements. You will frame the problem select or design the method define how success is measured and implement a solution of sufficient quality to run in production. You will work alongside a Data Engineer who owns the pipelines and platform which allows you to concentrate on the modelling is an applied role. Theoretical depth matters and so does the ability to deliver clean maintainable code that a colleague can extend without RESPONSIBILITIES Design develop and validate machine learning models across a range of problem domains and data evaluation criteria and testing strategy before development begins and measure performance against ambiguous business problems into well-defined analytical ones and select methods that are appropriate to the constraints rather than to and evaluate LLM and agentic systems including the guardrails required for enterprise data models and semantic structures that support reliable AI-driven with data engineering to move models into production and monitor their behaviour over findings methodology and limitations to technical and business REQUIREMENTS Bachelors degree in Computer Science Engineering Statistics or a related quantitative field or equivalent practical experience as a Data Scientist or Machine Learning Engineer including models deployed to production and maintained -level Python and experience with the modern machine learning stack including scikit-learn PyTorch and statsmodels or equivalent grounding in statistics probability and linear algebra sufficient to reason about uncertainty and model assumptions rather than only reporting knowledge of Databricks and/or Snowflake and experience operating in a Spark-backed with MLOps practice including experiment tracking model registry versioning monitoring and delivering in a major cloud environment with Azure preferred and AWS a strong software engineering habits including version control code review and automated written and verbal communication including the ability to explain and defend methodology to stakeholders who will challenge PERKS A fun work atmosphere that values equity diversity and contractor work environment and flexible scheduling.6-month contract with the possibility of extension.