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Data Scientist

Experience: 2 to 4 Years

Job Brief

We are looking for a detail-oriented and analytical Data Scientist with 2+ years of experience to analyze data, build machine learning models, and generate actionable insights to support business decisions. The candidate should have strong technical skills, problem-solving abilities, and a passion for working with data to solve real-world challenges.

Position: Data Scientist

Experience: 2 to 4 Years

Salary: Don’t worry about it, if you have right skills.

No. of Openings: Always open for the right candidate.

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Responsibilities & Duties

Key Responsibilities

Collect, clean, and analyze large datasets from multiple sources.
Develop, train, and implement machine learning and statistical models.
Perform Exploratory Data Analysis (EDA) to identify trends, anomalies, and patterns.
Create dashboards, reports, and visualizations for business stakeholders.
Translate business problems into data-driven solutions and actionable insights.
Work closely with Product, Engineering, and Business teams to deliver AI-powered solutions.
Optimize and improve model performance through experimentation and evaluation.
Automate data processing pipelines and analytical workflows.
Document methodologies, experiments, and maintain data integrity.
Develop and integrate Generative AI solutions using Large Language Models (LLMs) for business applications.
Design, build, and optimize RAG (Retrieval-Augmented Generation) pipelines for knowledge-based AI systems.
Implement prompt engineering techniques to improve LLM performance and reliability.
Build AI agents and workflow automation using frameworks such as LangChain and LangGraph.
Fine-tune, evaluate, and monitor LLM-based applications for production use.

Skill-set we are looking for

Requirements:

Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or a related field.
2+ years of experience in Data Science, Analytics, or Machine Learning.
Strong proficiency in Python (preferred)
Experience with libraries such as Pandas, NumPy, Scikit-learn, Matplotlib, and Seaborn.
Good understanding of machine learning algorithms including regression, classification, clustering, and ensemble methods.
Strong SQL skills for data extraction, transformation, and manipulation.
Experience with data visualization tools such as Power BI, Tableau, Excel, or Plotly.
Solid understanding of statistics and probability.
Good communication and analytical skills.
Knowledge of Large Language Models (LLMs), Generative AI concepts, Prompt Engineering, and AI application development.
Hands-on experience with LangChain, LangGraph, or similar LLM orchestration frameworks.
Understanding of Retrieval-Augmented Generation (RAG), vector databases, embeddings, and semantic search concepts.
Experience consuming and integrating AI APIs

Preferred Skills:

Experience with TensorFlow or PyTorch.
Exposure to cloud platforms such as AWS, GCP, or Azure.
Experience building APIs and data pipelines.
Understanding of big data tools such as Spark or Hadoop.
Experience with vector databases
Familiarity with LLM evaluation techniques, AI agents, function calling, and tool integration.
Knowledge of MLOps/LLMOps, model deployment, monitoring, and versioning.
Experience deploying AI applications using Docker, Kubernetes, or cloud-native AI services.

Key Competencies:

Strong problem-solving mindset.
Attention to detail and data quality.
Team collaboration and cross-functional communication.
Time management and ability to manage multiple priorities.
Ability to explain technical concepts and AI-driven insights to non-technical stakeholders.
Curiosity for emerging AI technologies and continuous learning in the Generative AI ecosystem.

Benefits you get

No bond/agreement
Flexible timing
Celebrations
5 days working
Medical insurance
Technical growth
18 paid leaves and 10 holidays
Paid subscriptions of channels
Games indoor
& outdoor
On time salary
Friendly environment
Work life balance