Data Scientist

Exploring data and building ML models to solve business problems

ML & AI Engineering Junior Middle Senior Lead / Staff Principal
Full Matrix Career Track PDF
78 skills
5 levels
101 mandatory
389 requirements

Data Scientist is a role in the ML & AI Engineering family. It has 78 skills across 5 levels (from Junior to Principal). 101 skills are mandatory. Key domains: Programming Fundamentals, Backend Development, Database Management.

Technology Stack

Junior Python 3.11+, pandas, numpy, matplotlib/seaborn, scikit-learn, Jupyter, SQL
Middle Python, scikit-learn, XGBoost/CatBoost/LightGBM, PyTorch basics, Optuna/Hyperopt, MLflow, SQL advanced, Spark basics
Senior PyTorch/JAX, Transformers (HuggingFace), Deep Learning advanced, Causal Inference, Bayesian methods, Spark, LLM fine-tuning
Lead / Staff DS Platform, Experiment tracking, Model governance, LLM orchestration (LangChain), Automated ML (AutoML)
Principal Research infrastructure, LLM strategy, Multi-modal AI, Publishing pipeline

Focus by Level

Junior

Exploratory Data Analysis (EDA). Building baseline models. Feature engineering. Data visualization. Preparing reports.

Middle

Formalizing business problems as ML tasks. Building and validating models. A/B testing. Presenting results to stakeholders.

Senior

Researching new approaches (NLP, CV, RecSys). Designing experiments. Publishing results. Mentoring. Cross-functional collaboration.

Lead / Staff

Data Science strategy. Prioritizing ML projects by business impact. Coordinating DS and Engineering. Experimentation standards.

Principal

AI research strategy. Conference publications. Building DS culture. LLM/GenAI adoption strategy.

Skill Matrix

78 skills × 5 levels. Click on a cell for details.

A Awareness W Working V Advanced E Expert

AI-Assisted Development

4 skills
Skills Jun Mid Sen Lead Princ
GitHub Copilot A W A E E
Cursor IDE A W A A
ChatGPT / Claude A W A E E
Prompt Engineering for Code A W A E E

API & Integration

3 skills
Skills Jun Mid Sen Lead Princ
REST API Design A W A E E
GraphQL Design A W A E E
API Documentation A W A E E

Architecture & System Design

1 skills
Skills Jun Mid Sen Lead Princ
System Design Fundamentals A W A E E

Backend Development

2 skills
Skills Jun Mid Sen Lead Princ
Python Web Frameworks A W A E E
Redis A W A E E

Cloud & Infrastructure

4 skills
Skills Jun Mid Sen Lead Princ
Docker A W A E E
Kubernetes Core A W A E E
AWS A W A E E
Network Fundamentals A W A E E

Data Engineering

6 skills
Skills Jun Mid Sen Lead Princ
Apache Spark A W A E E
Pandas / Polars A W A E E
SQL-based ETL A W A E E
Data Quality A W A E E
BI Dashboards A W A E E
Data Visualization A W A E E

Database Management

5 skills
Skills Jun Mid Sen Lead Princ
PostgreSQL A W A E E
Advanced SQL A W A E E
ClickHouse A W A E E
Database Indexing A W A E E
Query Optimization A W A E E

DevOps & CI/CD

1 skills
Skills Jun Mid Sen Lead Princ
GitHub Actions / GitLab CI A W A E E

Machine Learning & AI

35 skills

Observability & Monitoring

3 skills
Skills Jun Mid Sen Lead Princ
Structured Logging A W A E E
Prometheus & Grafana A W A E E
OpenTelemetry A W A E E

Programming Fundamentals

7 skills
Skills Jun Mid Sen Lead Princ
Algorithms & Complexity A W A E E
Data Structures A W A E E
OOP & SOLID Principles A W A E E
Design Patterns A W A E E
Multithreading A W A E E
Async Programming A W A E E
Code Quality & Refactoring A W A E E

Security

2 skills
Skills Jun Mid Sen Lead Princ
OWASP & Application Security A W A E E
Secure Coding Practices A W A E E

Testing & QA

3 skills
Skills Jun Mid Sen Lead Princ
Unit Testing A W A E E
Unit Testing A W A E E
Integration Testing A W A E E

Version Control & Collaboration

2 skills
Skills Jun Mid Sen Lead Princ
Git Advanced A W A E E
Code Review A W A E E

FAQ

What skills are needed for the Data Scientist role?

The Data Scientist role requires 78 skills, of which 101 are mandatory. Skills are distributed across 5 levels: from Junior to Principal. See full matrix.

How to advance to the next level in the Data Scientist role?

Use the Grade Calculator to assess your current level and get personalized recommendations. The system will show which skills need to be developed for the next level.

What tech stack is used in the Data Scientist role?

The stack includes 5 technologies at different levels. Python 3.11+, pandas, numpy, matplotlib/seaborn, scikit-learn, Jupyter, SQL, Python, scikit-learn, XGBoost/CatBoost/LightGBM, PyTorch basics, Optuna/Hyperopt, MLflow, SQL advanced, Spark basics, PyTorch/JAX, Transformers (HuggingFace), Deep Learning advanced, Causal Inference, Bayesian methods, Spark, LLM fine-tuning...

How does the community define requirements for the Data Scientist role?

Role requirements are shaped by the community through a proposal system. Any member can suggest changes that go through voting and expert review.

Community

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