Role Overview
Linkedin is hiring a mid-level Data Scientist (Predictive Modelling, 9+ years). This is a full-time role in Chhatrapati Sambhajinagar. Part of Linkedin's Lifecycle hiring. Full responsibilities, required qualifications, and the apply link are listed in the description below.
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Job Description
Tier 1 Top MNC is hiring for Senior Data Scientist with strong hands on Predictive Modelling.
Work Mode: Remote
Experience: 9-15 years
Salary: 50 LPA
Mandatory Skills: Generative AI Fundamentals, Statistics & Probability, Random Forest, LSTM, SVM, Advanced Python, SQL, Docker, Model Monitoring, CI/CD, Time Series Forecasting, Cloud Development
REQUIREMENTS
- Total experience 9+ years.
- Hands on working experience in data science with a focus on predictive modelling) (eg. Statistical Analysis, ANOVA, Time series Analysis, Regression Analysis) and optimization.
- Strong working experience with Data Science on GCP, Generative AI fundamentals.
- Strong experience with Python (and/or R) and libraries such as Pandas, NumPy, Scikit-learn.
- Strong knowledge of Cloud Architecture and deployment of data solutions in cloud ecosystems (e.g. AWS, Azure, GCP).
- Proven expertise in machine learning, mathematical optimization (e.g., LP, IP, genetic algorithms, RL), and NLP techniques.
- Familiarity with Generative AI fundamentals and hands-on experience with RAG, Lang Chain, Llama Index, and prompt engineering.
- Strong understanding of MLOps principles and tools for CI/CD, monitoring, and model lifecycle management.
- Excellent communication skills and the ability to collaborate effectively with cross-functional teams.
RESPONSIBILITIES
- Understanding the client’s business use cases and technical requirements and be able to convert them into technical design which elegantly meets the requirements.
Mapping decisions with requirements and be able to translate the same to developers.
- Identifying different solutions and being able to narrow down the best option that meets the client’s requirements.
- Defining guidelines and benchmarks for NFR considerations during project implementation
- Writing and reviewing design document explaining overall architecture, framework, and high-level design of the application for the developers
- Reviewing architecture and design on various aspects like extensibility, scalability, security, design patterns, user experience, NFRs, etc., and ensure that all relevant best practices are followed.
- Developing and designing the overall solution for defined functional and non-functional requirements; and defining technologies, patterns, and frameworks to materialize it
- Understanding and relating technology integration scenarios and applying these learnings in projects
- Resolving issues that are raised during code/review, through exhaustive systematic analysis of the root cause, and being able to justify the decision taken.
- Carrying out POCs to make sure that suggested design/technologies meet the requirements.
Frequently Asked Questions
How do I apply for the Data Scientist (Predictive Modelling, 9+ years) position at Linkedin?
Use the Apply button above to submit your application directly to Linkedin. Most applications take less than 5 minutes if your resume and contact details are ready, and you'll be routed to the employer's official application system to finish.
Where is the Data Scientist (Predictive Modelling, 9+ years) position at Linkedin located?
This position is based in Chhatrapati Sambhajinagar. Linkedin has not indicated remote or hybrid options for this role, so candidates should plan for on-site work.
What does a Data Scientist (Predictive Modelling, 9+ years) at Linkedin earn?
Linkedin has not disclosed a salary range in this posting. Many employers share specifics later in the interview process; you can also ask during a recruiter screen if compensation transparency is important to you.
When was the Data Scientist (Predictive Modelling, 9+ years) role at Linkedin posted?
This role was posted on May 3, 2026 (36 days ago). It's still listed as actively hiring; we re-confirm openings against the source system multiple times per day and remove closed roles.
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