Senior Data Scientist

Weekday AI (YC W21)

Chennai

On-site

INR 2,000,000 - 3,000,000

Full time

28 hours ago
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Job summary

Weekday AI (YC W21) in Bengaluru and Chennai seeks an experienced Senior Data Scientist to build scalable AI solutions, including RAG pipelines and AI agents. You will translate business needs into data-driven models and deploy production-grade ML systems.

The role requires strong Python skills, ML expertise, and hands-on work with cloud AI services, vector databases, and MLOps practices to deliver measurable business value.

Qualifications

  • 5+ years of experience in data science, analytics, machine learning, or applied AI.
  • Strong programming skills in Python, with hands-on experience developing production-grade data and AI applications.
  • Expertise in ML algorithms, including regression, classification, optimisation, and neural networks.
  • Strong understanding of statistical analysis, probability distributions, hypothesis testing, and experimental design.
  • Practical experience with Generative AI, LLMs, RAG, LangChain, LangGraph, or AutoGen.
  • Knowledge of vector databases, embeddings, retrieval systems, knowledge graphs, and AI agent architectures.
  • Experience with cloud AI/ML services such as AWS Bedrock and SageMaker, Azure OpenAI and AI Studio, or GCP Vertex AI and Gemini.
  • Familiarity with MLOps/LLMOps, CI/CD, Docker, Kubernetes, and event-driven systems.
  • Experience with relational databases, SQL, and NoSQL or big-data technologies such as MongoDB, Cassandra, or Hadoop.
  • Proficiency in data visualisation tools such as Tableau, Power BI, QlikView, or D3.js.
  • Strong analytical, problem-solving, communication, and stakeholder-management skills.
  • Ability to manage projects end to end, collaborate across teams, and mentor emerging talent.
  • A bachelors degree in Engineering, Computer Science, or a related analytical discipline is preferred; a relevant masters degree is an advantage.
  • A continuous-learning mindset and strong interest in Generative AI, AI safety, intelligent automation, and emerging technologies.

Responsibilities

  • Translate business challenges into analytical problems and deliver actionable, data-driven recommendations.
  • Collect, process, cleanse, and validate data to ensure accuracy, consistency, and analytical reliability.
  • Develop and optimise machine learning models, classifiers, predictive systems, and automation solutions.
  • Build AI-powered applications, including chatbots, RAG pipelines, workflow agents, and multi-agent systems.
  • Develop Python-based APIs and microservices integrating LLMs from OpenAI, Anthropic, AWS, Azure, and Google Cloud.
  • Design retrieval, embedding, inference, and knowledge-processing pipelines using vector databases and knowledge graphs.
  • Implement AI and machine learning workloads on AWS, Azure, and GCP using scalable cloud architectures.
  • Establish deployment, evaluation, monitoring, and retraining pipelines for production AI systems.
  • Apply infrastructure-as-code practices using tools such as Terraform and CloudFormation.
  • Develop automated anomaly detection systems, dashboards, and reporting solutions for continuous monitoring.
  • Conduct statistical analysis, hypothesis testing, experimentation, and exploratory data analysis.
  • Present findings, model outcomes, and recommendations clearly to clients and business stakeholders.
  • Ensure AI solutions follow appropriate security, governance, reliability, and responsible AI practices.
  • Participate in architecture discussions and code reviews while maintaining clean, maintainable code.
  • Manage project delivery, mentor junior team members, and contribute to recruitment and knowledge-sharing initiatives.

Skills

Python programming
Production-grade AI apps
Machine learning algorithms
Statistical analysis
Generative AI / LLMs
RAG pipelines
LangChain / LangGraph / AutoGen
Vector databases / embeddings
Cloud AI/ML services
MLOps / LLMOps
CI/CD
Docker / Kubernetes
SQL / NoSQL / big data
Data visualization (Tableau, Power BI,
QlikView / D3.js

Education

Bachelor's degree in Engineering / CS
Masters degree (advantage)

Tools

OpenAI / Anthropic / AWS / Azure / GCP services
Terraform / CloudFormation
MongoDB / Cassandra / Hadoop

Job description

Job Description:

This role is for one of the Weekdays clients

Salary range: Rs 2000000 - Rs 3000000 (ie INR 20-30 LPA)

Experience: 5+ yrs

Location: Bengaluru, Chennai

Job Type: Full-time

We are looking for an experiencedSenior Data Scientistwith strong expertise inPython, Machine Learning, Generative AI, Large Language Models (LLMs), and AI engineeringto develop intelligent, scalable, and data-driven solutions. The ideal candidate will combine statistical expertise and analytical thinking with practical experience building AI applications, retrieval-augmented generation (RAG) pipelines, AI agents, and production-ready machine learning systems.

You will work on complex business challenges, translating data and analytical requirements into innovative solutions that improve decision-making, automate workflows, and deliver measurable business value.

Key Responsibilities
  • Translate business challenges into analytical problems and deliver actionable, data-driven recommendations.
  • Collect, process, cleanse, and validate data to ensure accuracy, consistency, and analytical reliability.
  • Develop and optimise machine learning models, classifiers, predictive systems, and automation solutions.
  • Build AI-powered applications, including chatbots,RAG pipelines, workflow agents, and multi-agent systems.
  • Develop Python-based APIs and microservices integrating LLMs from OpenAI, Anthropic, AWS, Azure, and Google Cloud.
  • Design retrieval, embedding, inference, and knowledge-processing pipelines using vector databases and knowledge graphs.
  • Implement AI and machine learning workloads on AWS, Azure, and GCP using scalable cloud architectures.
  • Establish deployment, evaluation, monitoring, and retraining pipelines for production AI systems.
  • Apply infrastructure-as-code practices using tools such as Terraform and CloudFormation.
  • Develop automated anomaly detection systems, dashboards, and reporting solutions for continuous monitoring.
  • Conduct statistical analysis, hypothesis testing, experimentation, and exploratory data analysis.
  • Present findings, model outcomes, and recommendations clearly to clients and business stakeholders.
  • Ensure AI solutions follow appropriate security, governance, reliability, and responsible AI practices.
  • Participate in architecture discussions and code reviews while maintaining clean, maintainable code.
  • Manage project delivery, mentor junior team members, and contribute to recruitment and knowledge-sharing initiatives.
What Makes You a Great Fit
  • 5+ years of experiencein data science, analytics, machine learning, or applied AI.
  • Strong programming skills inPython, with hands-on experience developing production-grade data and AI applications.
  • Expertise in machine learning algorithms, including regression, classification, optimisation, and neural networks.
  • Strong understanding of statistical analysis, probability distributions, hypothesis testing, and experimental design.
  • Practical experience withGenerative AI, LLMs, RAG, LangChain, LangGraph, or AutoGen.
  • Knowledge of vector databases, embeddings, retrieval systems, knowledge graphs, and AI agent architectures.
  • Experience with cloud AI/ML services such asAWS Bedrock and SageMaker, Azure OpenAI and AI Studio, or GCP Vertex AI and Gemini.
  • Familiarity with MLOps/LLMOps, CI/CD, Docker, Kubernetes, and event-driven systems.
  • Experience with relational databases, SQL, and NoSQL or big-data technologies such as MongoDB, Cassandra, or Hadoop.
  • Proficiency in data visualisation tools such as Tableau, Power BI, QlikView, or D3.js.
  • Strong analytical, problem-solving, communication, and stakeholder-management skills.
  • Ability to manage projects end to end, collaborate across teams, and mentor emerging talent.
  • A bachelors degree in Engineering, Computer Science, or a related analytical discipline is preferred; a relevant masters degree is an advantage.
  • A continuous-learning mindset and strong interest inGenerative AI, AI safety, intelligent automation, and emerging technologies.
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