Data Scientist Lead

We are seeking a highly skilled and versatile Data Scientist to join our growing data team. This role combines capabilities in data engineering, machine learning, generative AI, statistics, and domain understanding. You will be responsible for designing and implementing end-to-end AI/ML workflows — from raw data ingestion to deploying scalable models — while working closely with cross-functional teams to drive data-powered decisions and intelligence across our platforms.

Responsibilities

• Design and implement robust ETL/ELT data pipelines for both structured and unstructured data
• Build interactive dashboards and visualizations to communicate insights effectively
• Develop, evaluate, and deploy machine learning and/or generative AI models for a variety of business use cases
• Apply statistical analysis and mathematical modeling to derive insights from complex datasets
• Collaborate with data engineers, analysts, software developers, and business teams to deliver data-driven solutions
• Build and maintain scalable ML pipelines and APIs for real-time and batch inference
• Ensure best practices in model versioning, reproducibility, observability, and governance (MLOps)
• Stay current with trends in AI/ML, including LLMs and GenAI applications
• Contribute to projects involving semantic search, knowledge graphs, or retrieval-augmented generation (RAG) as needed

Qualifications

Must have:

• 5+ years of hands‑on experience in Data Science, ML, or Applied AI

Technical Skills

• Proficiency in Python (e.g., Pandas, NumPy, FastAPI)
• Strong experience with SQL and working with relational and NoSQL databases
• Good knowledge of big data technologies (e.g., Spark, Databricks, Delta Lake, Kafka)
• Experience with at least one Cloud provider (e.g., Azure, AWS, or GCP)
• Experience using data visualization / BI tools such as Power BI, Tableau, or open-source BI tools
• Solid knowledge and hands-on experience with key machine learning algorithms such as classification, regression, clustering, time series forecasting, and anomaly detection using tools like Scikit-learn, PyTorch, and TensorFlow
• Strong foundation in machine learning concepts and deep learning (e.g., CNNs, RNNs, Transformers)

Math & Statistical Knowledge

• Strong foundation in probability, statistics, optimization, and linear algebra              
• Experience in designing experiments (e.g., A/B testing) and interpreting statistical significance
• Ability to apply math-driven thinking to AI/ML model design

Domain Knowledge

• Experience with one of the following domains such as media, banking, finance, healthcare, retail, manufacturing, or insurance
• Ability to understand and interpret domain-specific business problems and translate them into data science solutions

Soft Skills

• Strong problem-solving and critical thinking abilities
• Ability to clearly communicate technical findings to non-technical stakeholders
• Collaborative, agile mindset with a self-starter attitude
• Comfortable working in fast-paced, cross-functional teams

English Requirements

• Good communication skills in English, both written and verbal

Nice to have:

• Experience with ETLtools (Airflow, DBT, Azure Data Factory, or AWS Glue)
• Experience with MLOps tools (e.g., MLflow, SageMaker, Azure ML, Vertex AI)
• Generative AI Skills
• Awareness or working knowledge of LLMs (e.g., GPT-4, Claude, LLaMA, Mistral)
• Exposure to GenAI frameworks such as LangChain, LlamaIndex, or Hugging Face Transformers
• Understanding of prompt engineering, embeddings, and concepts like RAG
• Familiarity with GenAI use cases such as summarization, document analysis, chatbots, or code generation
• Ability to integrate GenAI APIs (OpenAI, Azure OpenAI, Hugging Face) into applications