Senior Data Scientist I, GenAI
Senior Data Scientist
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Senior Data Scientist Job Listings
Senior Data Scientist (Senior Data Scientist / Lead Data Scientist) job listings target candidates who can translate business goals into data-driven solutions and have experience in modeling and MLOps processes. Listings typically highlight data pipelines, feature engineering, experimental design, deploying models to production, and stakeholder management. The ability to demonstrate impact through metrics is highly valued.
What Does a Senior Data Scientist Do?
A Senior Data Scientist defines complex business problems using data and formulates hypotheses for solutions. They perform data cleaning, feature extraction, and model selection. They train, evaluate, and deploy machine learning models. They measure impact using A/B tests and causal inference methods. Working closely with data infrastructure, product, and engineering teams, they deliver scalable analytics solutions and provide mentorship to the team.
What to Look for in Senior Data Scientist Job Listings
Check if the problem focus is on product, growth, or risk. Data volume, freshness, and access layers should be clear. Feature store, model monitoring, versioning, and rollback strategies should be mentioned. Experimental platform, A/B test standards, and approval processes should be outlined. Production deployment path, MLOps tools, and responsibility distribution (Data Engineer, ML Engineer, Analytics) should be clearly stated.
Education and Certifications Required for Senior Data Scientists
Degrees in Statistics, Mathematics, Computer Science, Economics, or related master’s/PhD programs are preferred. Courses in machine learning, statistical modeling, and experimental design are valuable. Cloud data service certifications and MLOps training are a plus. Publications, conference presentations, Kaggle rankings, or production projects serve as strong proof of expertise.
Skills and Attributes Employers Are Looking For
Statistical thinking, causal reasoning, and experimental methodology are essential. Writing production-quality code, monitoring models, and debugging are important. The ability to translate business impact into metrics, storytelling, and stakeholder management are emphasized. Over time, depth in data governance, ethics and bias analysis, and cost-performance optimization is expected.
Career Opportunities for Senior Data Scientists
High demand exists in e-commerce, fintech, gaming, telecom, health, and SaaS companies. Projects may include fraud detection, recommendation systems, pricing, customer lifecycle analytics, and demand forecasting. Career progression can lead to Principal Data Scientist, Data Science Lead, or Product Analytics Lead roles.
How to Apply for Senior Data Scientist Roles
In your CV, clearly describe the problem definition, modeling approach, and business impact. Specify data volume, latency targets, and production deployment steps. Include notebooks, publications, and production-accepted model examples in your portfolio. In a brief cover letter, summarize the business objective, experimental strategy, and model monitoring/retraining plan. Prepare for interviews with case studies and system design scenarios.
Areas Where a Senior Data Scientist Can Work
Senior Data Scientists may work in product analytics, growth and marketing optimization, risk scoring, fraud detection, NLP, computer vision, time series, and causal inference projects. They collaborate with data platforms to build feature stores, integrate into real-time scoring, and monitor model health metrics.
Programming Languages and Tools Commonly Required
Python is the most common language, used for data processing, modeling, and MLOps. SQL is mandatory. Scala or Java may be required for big data and streaming pipelines. Common frameworks include scikit-learn, TensorFlow, PyTorch, XGBoost, and LightGBM. Orchestration and production tools such as Airflow, MLflow, Kubeflow, Docker, and CI/CD knowledge add value.
Senior Data Scientist I, GenAI
07.01.2026
Çek Cumhuriyeti
Deneyim: 6-8 Yıl
Type of Work: Tam Zamanlı
Work Location: Hibrit
Job Description
Do you want to work on complex and pressing challenges—the kind that bring together curious, ambitious, and determined leaders who strive to become better every day? If this sounds like you, you’ve come to the right place.
Your Impact
You’ll work with the OneData organization focused on building enterprise data capabilities to support the Firm’s data strategy.
Our team is distributed across multiple locations, including offices in North America and Europe. The OneData organization is dedicated to advancing the capabilities and applications of Generative AI within our firm, driving innovation, and delivering impactful AI solutions
As a member of the OneData organization, you will collaborate with the data teams team to deliver state-of-the-art generative AI automations.
You will experience what it’s like to develop a generative AI product with a firm-wide impact. You’ll join a cross-functional team of data scientists, engineers, designers, and product managers working on a high-priority initiative. Leveraging cutting-edge technology, we aim to revolutionize how we build data capabilities.
You will work hands-on with the latest multimodal LLMs, conducting experiments and deploying production pipelines that utilize generative models (such as GPT-like models) for automating data curation, data lineage, data quality checks, data products creation. This includes model training, fine-tuning, evaluation, and iteration, enhancing creativity and content generation.
Your Growth
You are someone who thrives in a high-performance environment, bringing a growth mindset and entrepreneurial spirit to tackle meaningful challenges that have a real impact.
In return for your drive, determination, and curiosity, we’ll provide the resources, mentorship, and opportunities to help you quickly broaden your expertise, grow into a well-rounded professional, and contribute to work that truly makes a difference.
When you join us, you will have:
- Continuous learning: Our learning and apprenticeship culture, backed by structured programs, is all about helping you grow while creating an environment where feedback is clear, actionable, and focused on your development. The real magic happens when you take the input from others to heart and embrace the fast-paced learning experience, owning your journey.
- A voice that matters: From day one, we value your ideas and contributions. You’ll make a tangible impact by offering innovative ideas and practical solutions, all while upholding our unwavering commitment to ethics and integrity. We not only encourage diverse perspectives, but they are critical in driving us toward the best possible outcomes.
- Global community: With colleagues across 65+ countries and over 100 different nationalities, our firm’s diversity fuels creativity and helps us come up with the best solutions. Plus, you’ll have the opportunity to learn from exceptional colleagues with diverse backgrounds and experiences.
- Exceptional benefits: In addition to a competitive salary (based on your location, experience, and skills), we offer a comprehensive benefits package, including medical, dental, mental health, and vision coverage for you, your spouse/partner, and children.
Your qualifications and skills
- 5+ years of experience as a Data Scientist
- Deep theoretical and practical knowledge of NLP, Transformers, LLMs, and Generative AI
- Required experience with OpenAI’s GPT suite, including previous experience with their multimodal LLMs: GPT4V, GPT4o
- Theoretical understanding of how LLMs can be leveraged to build classification models and recommendation systems
- Strong programming skills: well-versed with building end-to-end data models and pipelines in Python according to the best engineering practices
- Experience managing a Git repository - maintaining effective version control with organized & clean branching strategies
Skills
About Company
About McKinsey
McKinsey & Company is a global management consulting firm. We are the trusted advisor to the world's leading businesses, governments, and institutions.
We work with leading organizations across the private, public and social sectors. Our scale, scope, and knowledge allow us to address problems that no one else can. We have deep functional and industry expertise as well as breadth of geographical reach. We are passionate about taking on immense challenges that matter to our clients and, often, to the world.
We work with our clients as we do with our colleagues. We build their capabilities and leadership skills at every level and every opportunity. We do this to help build internal support, get to real issues, and reach practical recommendations. We bring out the capabilities of clients to fully participate in the process and lead the ongoing work.
