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Applications open Full-Time Job

Junior Data Scientist

Humanli

  • Jaipur, India
  • Competitive Package
  • 0-2 Years
  • Posted Today
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About the role

Humanli.AI is a Startup founded by Alumnus of IIM' Bangalore/ISB Hyderabad & IIM' Calcutta. We are democratizing and extending technology that were accessible & consumed only by MNC’s or Fortune companies to SME and Mid-size firms. We are pioneers in bringing Knowledge Management algorithms & Large Language Models into Conversational BOT framework.

Job Title: AI/ML Engineer

Location: Jaipur

Job Type: Full-time

Experience: 0-2 years

Job Description

We are looking for an experienced AI/ML & Data Engineer to join our team and contribute to the development and deployment of our AI-based solutions. As an AI/ML & Data Engineer, you will be responsible for designing and implementing data models, algorithms, and pipelines for training and deploying machine learning models.

Responsibilities

Design, implement, and deploy data models, algorithms, and pipelines for training and deploying machine learning models.

Work closely with data scientists and software engineers to develop and deploy machine learning models using modern AI/ML frameworks and technologies.

Develop and maintain scalable data pipelines and infrastructure for processing and analyzing large volumes of structured and unstructured data.

Ensure the integrity, accuracy, and security of data used in machine learning models.

Collaborate with cross-functional teams to identify and solve complex data engineering problems.

Stay up-to-date with the latest developments in AI/ML, big data, and cloud computing technologies.

Requirements

BTech in Computer Science.

0-2 years of experience in data engineering and machine learning.

Strong programming skills in Python and experience with AI/ML frameworks such as TensorFlow, PyTorch, or scikit-learn.

Generative AI- Understand and worked on concept of Gen AI like RAG/Agents, have used frameworks like Langchain

Experience with data warehousing and data management technologies such as SQL, NoSQL, Hadoop, and Spark.

Strong knowledge of data modeling, data preprocessing, and feature engineering techniques.

Experience with cloud computing platforms such as AWS, Azure, or Google Cloud Platform.

Excellent problem-solving skills and ability to work independently and collaboratively in a team environment.

Strong communication skills and ability to explain technical concepts to non-technical stakeholders.

Apply here

https://docs.google.com/forms/d/e/1FAIpQLSeoYsDQUqNu-sZrrfN-VAuLQb_A9MBH4FEcAVkBJEmLRzaLuQ/viewform?usp=publish-editor

Eligibility & process

Who can apply

Seniority: Entry level. Employment type: Full-time

Skills & stack

Python SQL AWS Azure GCP Machine Learning Generative AI / LLMs PyTorch

Selection process

Details are shared by the recruiter after shortlisting.

Prep kit

20 resources
Study material 4
Company-specific guides 4
Likely coding questions 4
Round-wise strategy 4
Round 1: Online Assessment (OA) Aptitude, Quantitative Logic & 2 Coding Problems Focus on accuracy and speed. Practice arrays, strings, and standard arithmetic puzzles.
Round 2: Technical Interview 1 Core Tech Stack (Python, SQL, AWS, Azure, GCP, Machine Learning, Generative AI / LLMs, PyTorch) & Live Code Tracing Explain your thought process aloud. Analyze time & space complexities before coding.
Round 3: System Design & Problem Solving Database Schemas, APIs & Architecture Basics Clarify edge cases, diagram schemas cleanly, and discuss scalability trade-offs.
Round 4: HR & Cultural Fit Discussion Humanli Core Values, Learning Agility & Offer Terms Demonstrate passion, strong communication, and readiness for full-time collaboration.
Technical questions 5
What is the difference between WHERE and HAVING clauses in SQL? Answer
Model answer: WHERE filters rows before any groupings are applied, while HAVING filters aggregated groups after GROUP BY has executed.
Explain SQL Window functions: ROW_NUMBER(), RANK(), and DENSE_RANK(). Answer
Model answer: ROW_NUMBER() assigns unique sequential integers. RANK() assigns identical ranks to ties and skips ranks. DENSE_RANK() assigns identical ranks to ties without skipping rank numbers.
How do you handle NULL and missing values during data cleaning in Python/Pandas? Answer
Model answer: Use .isna().sum() to identify missing values. Impute with mean/median using .fillna() or remove with .dropna(subset=[...]) depending on variance impact.
What is the difference between Star Schema and Snowflake Schema in Data Warehousing? Answer
Model answer: Star Schema has denormalized dimension tables directly connected to the central Fact table. Snowflake Schema normalizes dimension tables into sub-dimensions to minimize redundancy.
How do you calculate MoM (Month-over-Month) growth in SQL? Answer
Model answer: Use LAG(revenue, 1) OVER (ORDER BY month) to fetch the previous month's revenue and compute (revenue - prev_revenue) / prev_revenue * 100.
Behavioural & HR questions 3
Why do you want to join Humanli as a Junior Data Scientist?
Highlight Humanli's market reputation, recent tech innovations, and how your skills in Python directly solve their team's objectives.
Describe a challenging bug or academic project roadblock and how you resolved it.
Use the STAR method: Situation (project context), Task (what needed solving), Action (specific tools/logic applied), Result (quantifiable positive outcome).
How do you handle strict deadlines or sudden scope changes?
Explain your prioritization strategy, proactive communication with mentors/peers, and agile mindset.
Humanli Competitive Package
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