Senior Data Scientist

🔥 0 minutes ago

🇮🇪 Ireland – Remote

⏰ Full Time

🟠 Senior

📊 Data Scientist

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BMC Software

WebsiteLinkedInAll Job Openings

5001 - 10000 employees

Founded 1980

🏢 Enterprise

☁️ SaaS

🤝 B2B

💰 Series unknown on 2018-06

Enterprise • SaaS • B2B

BMC Software is a long-established enterprise software company that builds IT operations, service management, automation, and cloud/mainframe management solutions for other businesses. The company delivers enterprise-grade products and platforms (including on-premises and SaaS offerings) that help organizations monitor, manage, and automate IT services and infrastructure, and it increasingly emphasizes AI-driven capabilities and collaboration in its product portfolio.

📋 Description

• Independently design, develop, evaluate, and operationalize complex AI/ML solutions • Apply machine learning and statistical modeling to classification, regression, ranking, forecasting, clustering, anomaly detection, and enterprise agentic AI use cases • Develop and evaluate intent classification, semantic matching, agent/skill/tool ranking, and model-routing techniques • Estimate execution latency, token demand, inference costs, workload trends, and resource requirements • Conduct exploratory analysis, dataset preparation, feature engineering, hypothesis testing, and reproducible experiments • Evaluate commercial API and self-hosted open-weight models for accuracy, reasoning, instruction adherence, structured outputs, latency, throughput, and cost • Design prompts, few-shot examples, tool-calling prompts, and context assembly strategies • Design and optimize RAG parsing, chunking, metadata, embedding, retrieval, reranking, and context selection • Diagnose retrieval and generation failures and measure retrieval and answer-quality metrics • Assess and apply prompting, RAG, supervised instruction fine-tuning, SFT, LoRA, QLoRA, and comparable adaptation methods • Curate instruction datasets and holdout evaluations and validate fine-tuned model artifacts and adapters • Evaluate agent routing, MCP tool selection, workflow selection, planning, task completion, tool-call correctness, delegation, and failure recovery • Design golden datasets, holdout sets, human review protocols, LLM-as-judge calibration, and statistical comparison methods • Automate evaluations and regression checks for models, prompts, RAG, fine-tuning, routing, and agents • Implement reproducible experimentation, model evaluation, and lifecycle workflows with automated validation and production-readiness checks • Develop automated training, fine-tuning, benchmarking, and evaluation pipelines with model registries and artifact traceability • Define quality gates, regression tests, release-readiness criteria, monitoring, and remediation recommendations • Collaborate with AI Engineering, AI Quality, Platform Engineering, Product Management, and domain experts • Lead complex Data Science initiatives from problem formulation through production handoff • Translate business requirements into measurable AI/ML objectives • Mentor junior and mid-level Data Scientists and communicate complex concepts to technical and non-technical stakeholders • Build tools that help customers migrate from competitor products to BMC solutions, reducing manual effort and enabling accurate, timely migrations

🎯 Requirements

• 8+ years of relevant Data Science, Machine Learning, or Applied AI experience • Bachelor's degree in Machine Learning, Statistics, Data Science, Physics, Computer Science, or a related field, or equivalent education and industry experience • Advanced Python proficiency with Pandas, NumPy, scikit-learn, and PyTorch or TensorFlow; SQL and practical data preparation skills • Strong statistics, experimental design, hypothesis testing, ML validation, and applied classification, regression, ranking, clustering, forecasting, and anomaly detection knowledge • Hands-on LLM prompting, embeddings, model comparison, and RAG design/optimization, including chunking, retrieval, and reranking • Practical instruction fine-tuning or parameter-efficient model adaptation experience, with measurable baseline comparisons • Experience designing evaluation datasets, automated quality metrics, and statistical model/LLM/RAG experiments • Hands-on MLOps and LLMOps: experiment tracking, model/dataset/prompt versioning, reproducible pipelines, registries/artifacts, evaluation automation, quality gates, and monitoring • Working knowledge of agent planning, routing, tool calling, MCP, A2A, and multi-agent patterns • Understanding of inference latency, throughput, concurrency, token cost, and on-premises versus provider-hosted model tradeoffs • Familiarity with AWS and/or Kubernetes or Red Hat OpenShift (OCP), and collaboration with platform engineering • Clear communication, independent problem solving, cross-functional collaboration, and mentoring • Demonstrated ability to independently deliver complex AI/ML solutions, make sound technical decisions within assigned initiatives, and mentor other Data Scientists • Experience contributing to reusable modeling, evaluation, and MLOps/LLMOps practices within project teams • Nice-to-have: OpenSearch, Elasticsearch, FAISS, Milvus, pgvector, or similar retrieval platforms • Nice-to-have: LangGraph, OpenAI Agents SDK, Google ADK, CrewAI, or other agentic frameworks • Nice-to-have: MLflow, Kubeflow, Ragas, DeepEval, OpenJudge, LangSmith, or comparable tooling • Nice-to-have: vLLM, NVIDIA Triton, quantization, GPU memory sizing, or distributed inference • Nice-to-have: Python backend APIs, OpenTelemetry, and AI observability • Nice-to-have: AI safety, prompt injection evaluation, privacy, responsible AI, and model governance • Nice-to-have: Enterprise code understanding, legacy modernization, or domain-specific model adaptation • Nice-to-have: Agile practices and Atlassian Jira/Confluence • Master's degree in a related field is nice-to-have

🏖️ Benefits

• Benefits information is provided via the employer's benefits page; specific benefits are not listed in the posting • Occasional business travel may be required • Equal opportunity employment • Reasonable accommodation available during the application and hiring process

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