Senior Data Scientist Resume Sample

Dr. Aisha Johnson

aisha@johnson.sci

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(415) 555-0455

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linkedin.com/in/aisha-johnson-datascience

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github.com/aishajohnson

Senior Data Scientist

Senior Data Scientist with 8+ years leading ML strategy and building AI platforms. Drove ML initiatives generating $20M+ revenue, built ML platform serving 30+ models in production, and improved prediction accuracy by 65%. Expert in ML architecture, deep learning, and technical strategy. Mentor DS teams and drive AI strategy org-wide.

WORK EXPERIENCE

Senior Data Scientist

Jan 2021 – Present

Tech Unicorn (Pre-IPO)

ML Platform & Strategy: Architected ML platform serving 30+ production models processing 100M+ daily predictions, drove AI strategy generating $20M+ annual revenue across 5 product lines
Advanced ML & Research: Improved core recommendation model accuracy by 65% using transformer architecture, published 2 peer-reviewed ML papers, led research on novel deep learning techniques
Technical Leadership: Mentored 6 data scientists on ML best practices, established ML engineering standards and model governance framework adopted by 25-person DS team

Data Scientist II → Senior Data Scientist

Jul 2017 – Dec 2020

AdTech Scale-up (Series C)

ML Systems at Scale: Built real-time bidding ML system processing 50K predictions/sec, developed multi-task deep learning model improving CTR by 45% and conversion by 30%
Deep Learning & NLP: Developed BERT-based ad relevance model achieving 94% precision, built computer vision model for ad creative optimization (38% performance lift)
MLOps & Infrastructure: Established ML engineering practices: model versioning, monitoring, A/B testing framework, reduced model deployment time from 2 weeks to 2 days

SKILLS & COMPETENCIES

CERTIFICATIONS

Professional Machine Learning Engineer

Jun 2022

Google Cloud

EDUCATION

Ph.D. in Computer Science

2013-2017

Carnegie Mellon University

Pittsburgh, Pennsylvania

Machine Learning
Natural Language Processing

Tools to build your Senior Data Scientist resume

Copy and adapt these proven examples to create a resume that stands out.

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Resume Headlines

Use these attention-grabbing headlines to make a strong first impression.

Senior Data Scientist | ML Platform Architecture | $20M+ Revenue, 30 Models in Production

Senior Data Scientist | Deep Learning Expert | 65% Accuracy Improvement, Published Research

Staff Data Scientist | AI Strategy & Leadership | Mentoring 6+ Data Scientists

Senior Data Scientist | PyTorch, TensorFlow, NLP | Driving AI Innovation

Senior Data Scientist | ML Systems at Scale | 100M+ Daily Predictions

Senior Data Scientist | Research & Production | Transformer Architecture, MLOps

💡 Tip: Choose a headline that reflects your unique value proposition and matches the job requirements.

⚡

Power Bullet Points

Adapt these achievement-focused bullets to showcase your impact.

ML Platform Architecture & Strategy

• Architected ML platform serving 30+ production models processing 100M+ daily predictions with 99.95% uptime enabling $20M+ annual revenue across 5 product lines

• Drove AI strategy for company defining ML roadmap, evaluating technologies, and establishing ML practices adopted across 25-person data science team

• Built unified ML infrastructure on AWS SageMaker supporting model training, deployment, monitoring, and A/B testing reducing time-to-production from weeks to days

• Designed ML feature store and model registry enabling feature reuse across teams and improving model development velocity by 40%

Advanced ML Research & Innovation

• Improved core recommendation model accuracy by 65% using transformer architecture and attention mechanisms, increasing user engagement by 45%

• Published 2 peer-reviewed ML papers at top conferences (NeurIPS, ICML) on novel deep learning techniques advancing state-of-the-art

• Developed multi-task deep learning model jointly optimizing CTR (45% lift) and conversion (30% lift) outperforming single-task baselines

• Built computer vision model for ad creative optimization using CNNs achieving 38% performance lift and processing 1M+ images daily

Deep Learning & NLP at Scale

• Developed BERT-based ad relevance model achieving 94% precision serving 50M+ daily predictions with sub-100ms latency

• Built real-time bidding ML system processing 50K predictions/second using GPU acceleration and model quantization

• Implemented large language model (LLM) for content generation using GPT fine-tuning creating personalized content for 5M+ users

• Developed neural search system using sentence transformers and vector similarity improving search relevance by 55%

Technical Leadership & Mentorship

• Mentored 6 data scientists on ML best practices, model development, and research methodology, advancing 2 from DS II to Senior through structured development

• Established ML engineering standards including model governance, deployment practices, monitoring, and documentation adopted by 25-person DS team

• Led ML reading group and internal tech talks educating 40+ engineers on latest ML research and techniques

• Drove adoption of modern ML stack (PyTorch, Transformers, MLflow) training 15+ data scientists and improving team productivity by 35%

💡 Tip: Replace generic terms with specific metrics, technologies, and outcomes from your experience.

📝

Resume Writing Tips for Senior Data Scientists

Lead with ML Platform-Level Impact

Senior data scientists build platforms, not just models. Lead with: revenue scale ($20M+), models in production (30+), predictions served (100M+ daily), org-wide AI strategy. Show your work enables entire ML orgs and drives company success.

Demonstrate Research Depth and Innovation

Senior DS means pushing ML forward. Include: published papers (NeurIPS, ICML), novel techniques, state-of-the-art results (65% improvement), research leadership. Show you contribute to ML field, not just apply existing methods.

Showcase Deep Learning and Specialized Expertise

Senior requires deep technical expertise. Include: transformers, multi-task learning, NLP (BERT, GPT), computer vision, reinforcement learning. Show mastery of advanced ML—go beyond basics to cutting-edge techniques.

Quantify Team Building and Organizational Influence

Senior DS multiply through people. Quantify: data scientists mentored (6+), ML standards established, team adoption, publications, promotions enabled. Show you build ML teams and culture, not just models.

Position for Principal/Staff Data Science Track

List 15-20 skills spanning ML architecture, deep learning (expert), NLP (expert), computer vision, MLOps, research, leadership, strategy. Show you're not just executing—you're defining how ML works at your company.

🎯

Essential Skills & Keywords

Include these skills to optimize your resume for ATS systems and recruiter searches.

ML Architecture & Strategy

ML Platform Architecture AI Strategy ML System Design Model Governance ML Infrastructure Technical Roadmapping

Deep Learning (Expert)

PyTorch (Expert) TensorFlow (Expert) Transformer Architecture Multi-Task Learning Model Optimization Neural Architecture Search

NLP & Transformers (Expert)

BERT & GPT Large Language Models (LLMs) Transfer Learning Sentence Transformers Neural Search LLM Fine-Tuning

Computer Vision

Convolutional Neural Networks (CNNs) Image Classification Object Detection Image Processing Vision Transformers

ML Engineering & MLOps (Expert)

AWS SageMaker GCP Vertex AI MLflow Model Deployment at Scale Feature Stores Model Monitoring

Advanced Techniques

Causal Inference Reinforcement Learning Bayesian Methods Time Series (Advanced) Recommendation Systems Anomaly Detection

Programming & Data (Expert)

Python (Expert) PySpark SQL (Expert) Distributed Computing GPU Computing Model Optimization

Research & Leadership

Research & Publications Technical Leadership Mentorship Cross-Functional Collaboration Stakeholder Management Team Building

💡 Tip: Naturally integrate 8-12 of these keywords throughout your resume, especially in your summary and experience sections.

Why this resume works

Role-Specific Strengths

ML platform and strategy leadership: Built ML platform with 30+ models, $20M revenue—senior scope requires platform thinking org-wide
Technical strategy and decision-making: Drove ML architecture, framework choices, research direction—senior DS shapes AI strategy
Advanced AI and research depth: Published research, deep learning expertise, novel algorithms—demonstrates cutting-edge ML knowledge
Organizational ML leadership: Mentored 6 data scientists, established standards, led guild—senior DS multiplies impact through teams

✓ ATS-Friendly Elements

Senior-level keywords: "ML platform," "AI strategy," "deep learning," "research," "technical leadership"
Strategic verbs: Architected, Led, Drove, Established, Mentored, Published
Business impact: revenue generation, model accuracy, platform scale, team enablement
Technical depth: research, novel algorithms, advanced deep learning, MLOps at scale
8+ years experience with clear progression to senior level

✓ Human-Readable Design

Summary positions as ML technical leader: platform architecture, team mentorship, AI strategy
Metrics reflect senior scope: $20M revenue, 30 production models, 65% improvements, org-wide impact
Experience shows progression: DS I → DS II → Senior DS
Demonstrates influence: shaped ML architecture, drove strategy, mentored teams, published research
Balance deep technical work (research, novel algorithms) with leadership and strategy

💡 Key Takeaways

Senior data scientists architect ML platforms and drive AI strategy, not just build models
Quantify impact at scale: revenue generated, models in production, prediction improvements
Show technical leadership: drove ML architecture, established patterns, mentored DS teams
Demonstrate research depth: published papers, novel techniques, state-of-the-art results
Balance hands-on ML work with strategy, mentorship, and organizational influence

📈 Career Progression in Data Science

See how Data Science roles evolve from model development to ML strategy.

📊 Data Scientist I → 🤖 Data Scientist II → 🚀 Senior Data Scientist (Current)

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