About The Role
We are looking for a highly skilled Senior Data Scientist who can translate complex business problems into advanced analytical solutions. The ideal candidate combines deep expertise in statistical modeling, machine learning, and data engineering with a strong focus on Generative AI (GenAI), Large Language Models (LLMs), and Deep Learning. This role requires both technical leadership and strategic vision—from driving AI/ML innovation to mentoring junior team members, and collaborating across product, consulting, and engineering teams to bring AI-powered solutions to life. By applying your expertise in data science to the ad-server and retail media domains, you will contribute to delivering targeted and impactful advertising campaigns, optimizing ad inventory, and maximizing ROI for the organization.
Roles And Responsibilities
○ While technical proficiency in data manipulation, statistical modelling, and machine learning is crucial, the ability to apply these skills to solve real-world business problems is equally vital
○ Translate complex business challenges into analytical frameworks using statistical and ML methodologies.○ Apply AI/ML solutions to real-world business use cases across multiple industries.○ Extract insights from large-scale datasets to improve model accuracy, fairness, and relevance.
○ Strong expertise in statistical modelling, machine learning, deep learning, and NLP, with hands-on experience in LLMs and Generative AI (fi ne-tuning, RAG, prompt engineering).
○ Profi ciency in Python, PyTorch/TensorFlow, Hugging Face, and cloud-based ML platforms (AWS/GCP/Azure) with MLOps practices.○ Skilled in building scalable data pipelines and ML systems for training, evaluation, and deployment at scale.○ Solid grounding in Responsible AI principles including fairness, explainability, and bias mitigation.
- AI/ML & Generative AI Innovation
○ Lead the design, development, and deployment of scalable ML and DL solutions, with emphasis on LLMs and GenAI.
○ Build training, fine-tuning, evaluation, and serving pipelines for LLMs across use cases like content generation, summarization, semantic search, personalization, and multimodal AI.○ Drive applied research, incorporating the latest in GenAI and foundation models into production-ready systems.○ Ensure solutions are optimized for performance, security, reliability, and cost.
- Leadership & Collaboration
○ Provide technical and strategic leadership to cross-functional teams of Data Scientists and Analysts.
○ Collaborate with engineering and product teams to integrate AI solutions into customer-facing platforms.○ Mentor junior data scientists; set and promote best practices in MLOps, Responsible AI, and ML system design.○ Stay ahead of industry trends and incorporate them into roadmap planning.
- Project Management & Strategy
○ Drive the execution of business plans and projects○ Manage the continuous improvement of data science initiatives○ Direct the gathering and assessment of data for project goals○ Develop contingency plans and adapt to changing business needs
Required Skills & Qualifications
- A master's or doctoral degree in a relevant field such as computer science, statistics, mathematics, or data science is preferred. A strong academic background with coursework in machine learning, statistical modeling, data mining, and programming is valuable.
- 8-12 years of practical experience in data science, generative AI, machine learning, and analytics. Experience in relevant domains, such as e-commerce, advertising, or retail, may be advantageous.
- Minimum 3–4 years of deep, hands-on expertise in NLP, LLMs, and Generative AI.
- 2+ years of Demonstrated experience in leading projects and teams.
- Advanced Proficiency in Python is essential for data manipulation, statistical analysis, and machine learning model development.
- Core Skills:
- Strong foundation in machine learning, deep learning, and NLP.
- Hands-on experience with LLMs (GPT, LLaMA, Falcon, Mistral, etc.) and GenAI frameworks (LangChain, Hugging Face, RAG, fine-tuning, LoRA).
- Profi ciency in Python, PyTorch/TensorFlow, SQL, and cloud platforms (GCP/AWS/Azure).
- Experience with MLOps frameworks (MLfl ow, Kubefl ow, Vertex AI, SageMaker, etc.).
- Strong data engineering skills to build ETL pipelines for large-scale datasets.
- Statistical rigor: hypothesis testing, power analysis, confidence intervals; regression (GLM/GLMM), time-series; causal inference (propensity scores, DiD, RDD) for business impact.
- Soft Skills:
○ Strong business acumen and ability to map AI/ML solutions to strategic goals.
○ Excellent communication and stakeholder management skills.○ Proven track record of mentoring and leading teams, collaborating with cross-functional teams, and communicating effectively with stakeholders.Skills: data science,machine learning,ml,generative ai,ai,nlp,llms,project,python,deep learning,teams,gpt,llama,falcon,mistral,langchain,hugging face,rag,fine-tuning,lora,sql,pytorch,tensorflow,gps,aws,azure,mlops,etl pipelines
