1 Opening(s)
3.0 Year(s) To 5.0 Year(s)
18.00 LPA TO 24.00 LPA
About the Role :
We are looking for a hands-on Full Stack Data Scientist who can independently manage the
entire machine learning lifecycle—from data wrangling to deployment—without relying on a
dedicated data engineering team. This role is ideal for someone who thrives in a fast-paced, self-
directed environment and is passionate about building real-world ML solutions that drive
business outcomes.
Key Responsibilities :
∙Own the full ML pipeline: data ingestion, cleaning, feature engineering, model
development, deployment, and monitoring.
∙Build and fine-tune models using Python and frameworks like Scikit-learn, XGBoost,
TensorFlow, or PyTorch.
∙Deploy models using Databricks, MLflow, and cloud-native tools (preferably Azure).
∙Develop robust, scalable pipelines using PySpark or native Databricks workflows.
∙Collaborate with BI analysts and business stakeholders to translate requirements into
production-ready solutions.
∙Maintain and improve existing models and pipelines with minimal supervision.
Required Skills :
∙3+ years of experience in applied data science or ML engineering.
∙Strong Python programming skills, including experience with data manipulation and ML libraries.
∙Experience with Databricks and cloud-based ML deployment (Azure preferred).
∙Ability to work independently across the full stack of ML development and deployment.
∙Familiarity with version control (Git), CI/CD, and MLOps best practices.
∙Excellent communication skills and ability to work with remote teams across time zones.
Nice to Have
∙Experience with data pipeline development using PySpark or Delta Lake.
∙Exposure to Docker, REST APIs, or real-time inference.
∙Prior experience working in a manufacturing or industrial analytics environment.
Interview Process:
Shortlisted candidates will be required to complete:
∙An online technical skills assessment focused on Python and applied machine learning.
∙An in-person practical test at our Ahmedabad Tech Center to evaluate real-world
problem-solving and deployment capabilities.
Hours: 2:30 PM – 11:30 PM IST (working from Office)
Reports to: Manager, Data Analytics California, USA
7 Opening(s)
5.0 Year(s) To 8.0 Year(s)
10.00 LPA TO 18.00 LPA
. Data Scientist – KMPL Support Services – Analytics
Location: Mumbai
Grade: M1 to M4
Reports to: Lead/Principal Data Scientist
Role Overview: Responsible for building analytical models for the banking, NBFC, and insurance sectors. Utilize machine learning algorithms or statistical models to optimize business processes across the customer lifecycle.
Key Responsibilities:
Develop and deploy machine learning ...
2 Opening(s)
3.0 Year(s) To 9.0 Year(s)
1.00 LPA TO 25.00 LPA
Please find the details below
Position : Data Scientist
Location : Work from home
Experience requirement : 3+ Years
Joining Date : Immediate to 30 days
Job Description
We are seeking a highly skilled and experienced Data Scientist to join our dynamic team. As a Data Scientist, you will play a critical role in analysing complex data sets, developing cutting-edge ...
1 Opening(s)
4.0 Year(s) To 15.0 Year(s)
30.00 LPA TO 90.00 LPA
Job Role : Data Scientist
Exp : 4+ Years
Location: Singapore ( onsite)
Qualifications:
Experience with ML models is a must Proven experience as a Data Scientist, Data Analyst, or similar role, specifically in the Telecom domain or with/for a Telecom company involved in OPEX analysis. Strong knowledge of statistical analysis, data modeling, machine ...
1 Opening(s)
4.0 Year(s) To 15.0 Year(s)
30.00 LPA TO 90.00 LPA
Job Role : Data Scientist
Location: Tokyo, Japan ( onsite)
Exp: 4+ Years
Experience with ML models is a must Proven experience as a Data Scientist, Data Analyst, or similar role, specifically in the Telecom domain or with/for a Telecom company involved in OPEX analysis. Strong knowledge of statistical analysis, data modeling, machine ...
1 Opening(s)
5.0 Year(s) To 10.0 Year(s)
0.00 LPA TO 0.00 LPA
We have an urgent opening for the position of Data Scientist for a reputed Company at Dubai location.
Company Profile: Established in 1999, the Company is a global provider of digital transformation solutions in the areas of Predictive Analytics, Digital Experience, and Digital Supply Chain Management, and has delivered solutions in 20 countries across North ...
5 Opening(s)
7.0 Year(s) To 12.0 Year(s)
14.00 LPA TO 24.00 LPA
Hello ,
Greetings from MM Management !! I am krishna kanth from MM Management, MM Management is into global recruitment services providing manpower across the globe.
About company- Company is an adept and reliable technology solutions provider focusing on Enterprise Digital Transformation for Software and Service Innovations and Business Process Management applications. Since our ...
4 Opening(s)
5.0 Year(s) To 8.0 Year(s)
8.00 LPA TO 13.00 LPA
JD-Data Scientist
>5 years of experience
For machine learning, data science and analytics models",,University Degree in Data Science, (Business) Informatics or similar",,License or Certificate required in Data Analyst/ Data Science /OSIsoft - PI/Power BI/RPA Align, SAP and advanced Excel",,Significant knowledge in advanced analytics such as Machine Learning,Stochastic Optimization, Operations Research and Simulation",,Proven ...
3 Opening(s)
7.0 Year(s) To 8.0 Year(s)
1.00 LPA TO 24.00 LPA
Please find the details below
Position : Data Scientist
Location : Bangalore
Experience requirement : 7-8 Years
Joining Date : Immediate to 15 days
Job Description
Develop, maintain, and optimize forecasting Machine Learning (ML) models for better accuracy. Collaborate with other data scientists and data engineers to ensure that specifications are translated into flexible, scalable, and maintainable solutions.
Research and stay ...
1 Opening(s)
2.0 Year(s) To 12.0 Year(s)
7.00 LPA TO 34.00 LPA
Data Scientist – Banking and Risk Management
Role Summary:
The Data Scientists will design AI/ML models for banking and risk management, driving innovation and enhancing operational efficiencies for financial institutions.
Key Responsibilities:
Develop AI/ML models for credit scoring, fraud detection, and risk assessment in banking.
Analyze large datasets from banking systems to identify risk ...