Posted:1 day ago|
Platform:
On-site
Full Time
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 .
Your role in building ML algorithms for the ad server and retail media would involve the following:
● Business Problem Solving
○ 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.
● Technical Proficiencies:
○ Strong expertise in statistical modelling, machine learning, deep learning, and NLP, with hands-on experience in LLMs and Generative AI (fine-tuning, RAG, prompt engineering).
○ Proficiency 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
● 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.
● 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).
● Proficiency in Python, PyTorch/TensorFlow, SQL, and cloud platforms (GCP/AWS/Azure).
● Experience with MLOps frameworks (MLflow, Kubeflow, 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.
○ 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.
MacroHire
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