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REQUIREMENT_ID_182 โ€ข 3-DAY_ACTIVE_POLICY

Associate Data Scientist

Company
Company fortive.eightfold.ai
Type
Opportunity Type Full-Time Job
Salary
Stipend / Salary 6 LPA - 12 LPA (eligible for performance bonus)
Location
Location Bengaluru East, Karnataka, India
Posted Date
Posted Date Today
Python SQL Pandas NumPy Statistics Machine Learning Data Visualization Scikit-learn TensorFlow PyTorch Azure AWS Google Cloud Generative AI LLMs
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Aptitude and Reasoning Practice Open Resource โ†—
Helps you sharpen quantitative and logical reasoning skills often tested in the initial screening round.
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Company Interview Preparation Hub Open Resource โ†—
Provides curated interview experiences, sample questions and tips specific to technology roles like data science.
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Comprehensive Interview Guides Open Resource โ†—
Offers detailed roadmaps, mock interview scripts and subjectโ€‘wise study plans useful for Fortiveโ€™s technical rounds.
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Algorithm Practice Platform Open Resource โ†—
Contains a wide range of coding problems to practice Python and dataโ€‘structure algorithms required for the online test.

Bachelorโ€™s degree (or equivalent) in Data Science, Computer Science, Statistics, Mathematics, Engineering or related technical discipline; Minimum 60% aggregate (or CGPA 6.5/10); No active backlogs at the time of joining; Graduation batch 2024, 2025 or 2026; Strong academic projects or internships in data science/ML preferred.

1
Round 1: Online coding assessment (Python/SQL)
2
Round 2: Technical interview (ML concepts, project discussion, case study)
3
Round 3: HR interview (fit, motivation, compensation discussion)
Fortive is a global industrial technology leader that builds solutions to make the world safer, healthier and more productive. With a portfolio spanning workplace safety, healthcare, predictive maintenance and industrial automation, Fortive operates in more than 50 countries and serves Fortune 500 customers. The companyโ€™s culture is built around continuous learning, collaboration and a relentless focus on delivering measurable impact for its clients. For fresh talent, Fortive offers a fastโ€‘paced environment where you can work on realโ€‘world problems, interact with senior engineers, and see the direct business outcomes of your work. The Associate Data Scientist role sits within Fortiveโ€™s Artificial Intelligence and Automation team in Bengaluru. This is an earlyโ€‘career position designed for candidates with 0โ€‘2 years of experience who have a solid grounding in statistics, machine learning and Python programming. You will be part of a crossโ€‘functional squad that partners with data engineers, ML engineers and business stakeholders to turn raw data into actionable insights. The role blends traditional analytics with cuttingโ€‘edge Generative AI and Large Language Model (LLM) projects, giving you exposure to both classic predictive modeling and nextโ€‘generation AIโ€‘driven solutions. **Key Responsibilities** 1. Perform exploratory data analysis and data cleaning on large, heterogeneous datasets. 2. Develop, train and evaluate supervised and unsupervised machineโ€‘learning models using Scikitโ€‘learn, TensorFlow or PyTorch. 3. Build and maintain dashboards and visualisations to communicate insights to nonโ€‘technical stakeholders. 4. Design and run A/B tests or experiments to validate model impact on business metrics. 5. Prototype Generative AI useโ€‘cases, including prompt engineering for LLMs. 6. Write efficient SQL queries to extract and transform data from relational databases. 7. Collaborate with data engineers to ensure data pipelines are reliable and scalable. 8. Document model assumptions, performance metrics and deployment procedures. 9. Participate in code reviews and contribute to the teamโ€™s MLOps best practices. 10. Stay updated with emerging AI trends and suggest innovative applications for Fortifyโ€™s product suite. **Tech Stack**: Python, SQL, Pandas, NumPy, Scikitโ€‘learn, TensorFlow/PyTorch, Azure/AWS/GCP, PowerBI/Tableau, Git, Docker. **Growth Path**: Starting as an Associate Data Scientist, you can progress to Data Scientist, Senior Data Scientist, Machine Learning Engineer, AI Engineer, or Analytics Engineer within 3โ€‘5 years, depending on performance and skill development. The roleโ€™s exposure to enterpriseโ€‘scale AI projects and cloud platforms accelerates career growth. **Why Join Fortive?** Fortive offers a blend of stability from a multinational corporation and the agility of a techโ€‘forward environment. You will work on highโ€‘impact projects that directly influence Fortuneโ€‘500 customers, receive mentorship from seasoned AI professionals, and benefit from a compensation package that includes a performance bonus and opportunities for continuous upskilling.

fortive.eightfold.ai โ€” Data Analytics & SQL Interview Guide

Previously asked questions, exam syllabus, coding benchmarks & round strategy.

APTITUDE & LOGIC ๐Ÿ“–
Aptitude Practice Questions & Online Mock Tests

Curated logical, quantitative, and verbal reasoning problems to sharpen reasoning skills required for the initial screening test.

Open Resource โ†—
COMPANY GUIDE ๐ŸŽฏ
fortive.eightfold.ai Interview Preparation Corner

Comprehensive guide covering typical interview formats, common questions, and preparation tips for fortive.eightfold.ai and off-campus tech roles.

Open Resource โ†—
MOCK TESTS & PAPERS ๐Ÿ“
Comprehensive Interview Prep Resources & Syllabus

Collection of previous year questions, company-specific test patterns, and interview experiences for technical and HR rounds.

Open Resource โ†—
CODING PRACTICE ๐Ÿ’ป
Algorithm and Data Structure Problem Set

Practice problems to improve coding proficiency and algorithm problem-solving speed for technical rounds.

Open Resource โ†—
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, Pandas, NumPy, Statistics, Machine Learning, Data Visualization, Scikit-learn, TensorFlow, PyTorch, Azure, AWS, Google Cloud, Generative AI, LLMs) & 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
fortive.eightfold.ai Core Values, Learning Agility & Offer Terms
Demonstrate passion, strong communication, and readiness for full-time collaboration.
What is the difference between WHERE and HAVING clauses in SQL? Answer โ–ผ
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 โ–ผ
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 โ–ผ
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 โ–ผ
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 โ–ผ
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.
Why do you want to join fortive.eightfold.ai as a Associate Data Scientist?
Preparation Tip: Highlight fortive.eightfold.ai'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.
Preparation Tip: 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?
Preparation Tip: Explain your prioritization strategy, proactive communication with mentors/peers, and agile mindset.

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