About this Data Scientist role at Weekday AI
๐ง๐ต๐ถ๐ ๐ฟ๐ผ๐น๐ฒ ๐ถ๐ ๐ณ๐ผ๐ฟ ๐ผ๐ป๐ฒ ๐ผ๐ณ ๐๐ต๐ฒ ๐ช๐ฒ๐ฒ๐ธ๐ฑ๐ฎ๐'๐ ๐ฐ๐น๐ถ๐ฒ๐ป๐๐
๐ฆ๐ฎ๐น๐ฎ๐ฟ๐ ๐ฟ๐ฎ๐ป๐ด๐ฒ: ๐ฅ๐ ๐ฏ๐ฑ๐ฌ๐ฌ๐ฌ๐ฌ๐ฌ - ๐ฅ๐ ๐ฑ๐ฑ๐ฌ๐ฌ๐ฌ๐ฌ๐ฌ (๐ถ๐ฒ ๐๐ก๐ฅ ๐ฏ๐ฑ-๐ฑ๐ฑ ๐๐ฃ๐)
Experience: 5+ yrs
Location: Bengaluru
Job Type: Full-time
We are looking for an experiencedย Data Scientistย with strong expertise inย Python and Large Language Models (LLMs)to develop intelligent, data-driven solutions that address complex business and product challenges. The role combines advanced analytics, machine learning, generative AI, and software engineering to build scalable solutions that deliver measurable business value.
The ideal candidate will be comfortable working across the full data science lifecycle, from problem definition and data exploration to model development, experimentation, deployment, and performance monitoring.
Requirements
Key Responsibilities
- Design, develop, and deploy data science and machine learning solutions usingย Python.
- Analyse large and complex datasets to identify meaningful patterns, trends, and actionable insights.
- Develop predictive models, statistical models, classification, regression, clustering, and other machine learning solutions.
- Work extensively withย Large Language Models (LLMs)ย to develop generative AI and NLP-based applications.
- Build solutions involving prompt engineering, embeddings, retrieval-augmented generation (RAG), text classification, summarisation, and information extraction.
- Evaluate and compare LLMs and machine learning approaches based on accuracy, relevance, latency, scalability, and cost.
- Develop data pipelines and preprocessing workflows for structured and unstructured data.
- Integrate AI/ML models and LLM capabilities into production applications through APIs and services.
- Conduct experiments, hypothesis testing, model evaluation, and performance optimisation.
- Collaborate with software engineers, product managers, analysts, and business stakeholders to understand requirements and define solutions.
- Translate business problems into measurable data science and machine learning objectives.
- Build prototypes and proof-of-concepts and take successful solutions toward production.
- Monitor model performance and identify opportunities for continuous improvement.
- Maintain clean, reusable, well-tested, and production-ready Python code.
- Document methodologies, experiments, models, and technical decisions.
- Stay current with developments in generative AI, LLMs, machine learning, NLP, and emerging data science technologies.
What Makes You a Great Fit
- 5+ years of professional experienceย in data science, machine learning, AI, or a closely related field.
- Strong hands-on expertise inย Pythonย for data science, machine learning, automation, and application development.
- Strong practical experience working withย LLMs and Generative AI.
- Good understanding of machine learning algorithms, statistical modelling, feature engineering, and model evaluation.
- Experience with NLP and unstructured text data.
- Strong understanding of LLM concepts includingย prompt engineering, embeddings, vector search, RAG, and model evaluation.
- Experience with machine learning and data science libraries such asย Pandas, NumPy, Scikit-learn, PyTorch, or TensorFlow.
- Experience working with SQL and relational or NoSQL databases.
- Ability to build scalable data pipelines and integrate models into production systems.
- Strong analytical, problem-solving, and experimentation skills.
- Experience with cloud-based AI/ML environments such asย AWS, Azure, or GCPย is an advantage.
- Familiarity with MLOps, model deployment, APIs, Docker, or CI/CD practices is desirable.
- Excellent communication skills with the ability to explain technical findings and AI concepts clearly.
- Strong ownership mindset and ability to independently drive data science initiatives from experimentation through delivery.
- Bachelor's or Master's degree inย Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related disciplineย is preferred.