About this template
The ATS Coordinate Axis template uses a mono layout (JetBrains Mono) with a discreet emerald X/Y axis in the left margin that materialises the chronology as a graph. The graduations are CSS divs, never images — the axis is only a visual marker and the CV text remains a linear flow that Workday, Avature and Mercury parse without incident. The scientific register signals quantitative thinking immediately.
Who is it for?
It suits data scientists, quants, ML engineers, statisticians, data science researchers and analytics translators applying at Goldman Sachs Quants, Morgan Stanley Quant Strategies, Citadel, Two Sigma, Renaissance Technologies, D.E. Shaw, Jane Street, Hudson River Trading, Anthropic, OpenAI, Databricks, Snowflake, Datadog, or to research labs (MIT CSAIL, Stanford AI Lab, DeepMind, FAIR Meta) recruiting via institutional portals.
How to use it
Create a dense 'Tech stack' section: Languages (Python, R, Scala, Julia), ML frameworks (PyTorch, TensorFlow, JAX, scikit-learn), Cloud (AWS Sagemaker, GCP Vertex, Azure ML), Data tools (dbt, Airflow, Spark, Kafka), Viz (Plotly, Tableau, Looker, Streamlit). For bullets, articulate impact in model AND business metrics: 'Improved fraud-detection model AUC from 0.78 to 0.91 — false positive reduction of 34% — $2.1M/year operational savings'. Mention Kaggle Master/Grandmaster status if applicable.
Frequently asked questions
Does the decorative coordinate axis break ATS parsing?
No. The axis and graduations are CSS elements positioned absolutely with border-left and pseudo-elements — no text is attached to them. Workday (used by Goldman Sachs, Morgan Stanley), Avature (JPMorgan, BlackRock) and academic ATS systems parse the document as a linear text flow. The scientific visual rendering remains for the human eye.
Compatible with quantitative finance ATS pipelines?
Yes. The major investment banks (Goldman Sachs, Morgan Stanley, JPMorgan, Citi) and quant funds (Citadel, Two Sigma, Renaissance, D.E. Shaw, Jane Street) use Workday, Avature, Mercury or proprietary systems. Critical acronyms (CFA, CQF, FRM, PRMIA, PhD Stats, MIT Sloan Quant, Princeton ORFE) are indexed as seniority keywords in quant recruitment pipelines.
Suitable for data science and machine learning roles?
Yes, that is its primary target. The mono register signals to Lead Data and engineering managers that you live in Jupyter and VSCode. List frameworks by category, mention open-source ML contributions (scikit-learn, HuggingFace, PyTorch) and link your Kaggle profile if you are Expert/Master/Grandmaster — these are strong markers in data science sourcing.
