Go

programming language, golang
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The pragmatic engineer’s choice for building scalable, efficient, and maintainable systems. Designed with simplicity and performance in mind, Go is a great fit for data engineers tackling high-throughput pipelines, distributed systems, or lightweight microservices. Its strong concurrency model (goroutines, channels) makes it ideal for handling parallel workloads, while its minimal runtime overhead ensures speed without the verbosity of C++ or the baggage of Java.
However, Go’s simplicity can feel spartan. No generics (until recently), no exceptions, and a strict focus on “the Go way” can frustrate those coming from more expressive languages. Its ecosystem is solid but lacks the rich libraries of Python or Java, making some tasks (e.g., advanced ML or data wrangling) less convenient.
Use Go when you need clean, performant code that’s easy to maintain. Skip it for heavy data science or one-off scripts. It’s not flashy, but it gets the job done—efficiently, if a bit rigidly.

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data scientist

Go-to-Market Enablement Manager (Sales Enablement) @ databricks

JP | 2025-12-27
Databricks' Go-to-Market Enablement Manager for Japan is a strategic, cross-functional role that leans heavy on program management, stakeholder diplomacy, and revenue-focused learning at scale.... read more »
Databricks, Go, Management, AI/ML, SaaS, Analytics, Data Lakehouse, Spark, Delta
data scientist

Data Scientist, Digital Advertisement/Marketing - Global Ad Technology Supervisory Department (GATD) @ rakuten

JP | 2025-12-27
Rakuten’s GATD is hiring a data scientist to own end-to-end ad delivery optimization—from hypothesis, feature engineering, and offline evaluation to online deployment, A/B testing, calibration,... read more »
Marketing, Management, Big Data, AI/ML, KPI, MLOps, GCP, Dataflow, Cloud Computing, BigQuery, SQL, Terraform, Ansible, Python, Go, Pandas, NumPy, DataViz, Spark, Analytics, Data Quality, Computer Science, GenAI, Data Streaming, Kafka, Flink, Beam, CI/CD, Docker, Kubernetes, AWS, Azure
promoted

O'Reilly: Building AI Agents with Model Context Protocol (MCP)

Design and implement composable agent architectures using MCP. Understand the MCP architecture and how it enables AI applications to access external context. Build MCP servers that expose tools, resources, and prompts to LLMs.

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data scientist

Enterprise Account Executive, Japan @ anthropicresearch

JP | 2025-12-26
Anthropic wants an Enterprise Account Executive in Tokyo to drive frontier AI adoption across Japan, owning the full cycle from prospecting to close and translating cutting-edge capabilities into... read more »
AI/ML, C, Go, Cloud Computing, Data Analytics, Computer Science
data scientist

Solution Architect (Data & AI) @ london-stock-exchange-group

JP | 2025-12-25
Bridge-builder role that straddles pre-sales and delivery, with GenAI at the core. In Tokyo, you translate business needs into prototypes and POCs that pair Generative AI with financial datasets... read more »
GenAI, LLM, Cloud Computing, Azure, AWS, GCP, Databricks, Snowflake, Fabric, AI/ML, API, Data Streaming, RAG, Python, SQL, Git, GitHub, CI/CD, Data Science, TensorFlow, PyTorch, Management, Data Engineering, Analytics, Go