1 Opening(s)
10.0 Year(s) To 15.0 Year(s)
Not Disclosed by Recruiter
JOB SUMMARYLooking for highly skilled and experienced Senior Data Architect. As a Senior Data Architect,you will play a critical role in designing, implementing, and managing data architecture,ensuring it supports both current needs and future aspirations in data and AI. This rolerequires a deep understanding of data architecture principles, data modelling ...
2 Opening(s)
2.0 Year(s) To 3.0 Year(s)
0.00 LPA TO 0.00 LPA
Key Responsibilities
Model Development & Training
○ Design, train, and fine-tune deep learning and machine learning models (transformers, CNNs, RNNs, gradient boosting, etc.).
○ Implement data preprocessing pipelines, feature extraction, and
augmentation techniques.
○ Conduct hyperparameter optimization and experiment management. ● Evaluation & Optimization
○ Run model evaluations, benchmark against baselines, and perform ablation studies.
○ ...
1 Opening(s)
3.0 Year(s) To 7.0 Year(s)
15.00 LPA TO 30.00 LPA
Key Responsibilities: - 1. Model Development: Design, build, and optimize supervised, unsupervised, and deep learning models for various business problems. 2. Data Exploration & Feature Engineering: Clean, transform, and analyze structured and unstructured data; identify significant features. 3. AI Integration: Develop end-to-end AI pipelines and integrate models into production systems ...
2 Opening(s)
2.0 Year(s) To 3.0 Year(s)
Not Disclosed by Recruiter
Job description
Role: MEP Modeler
Requirement: 2 candidates.Skill: Revit software, AutoCAD.
LOD: UPTO 500.working Days - 5.5Days (2 alternate Saturday off - 2nd and 4th) working Days - 6 days
working time - 9:30 am to 6pm
working mode- work from office
Key Responsibilities:
BIM Model Development: Develop detailed 3D BIM models of mechanical systems using industry-standard software such as ...
6 Opening(s)
2.0 Year(s) To 12.0 Year(s)
10.00 LPA TO 25.00 LPA
Credit Risk Analytics and Modelling – Analyse, model, validate and document various measures of Credit Risk for use in Expected Credit Loss and Capital computations.
Hands-on experience in building, implementing, documenting, monitoring, validating, refining models and scorecards – in particular for PD, LGD, EAD and related Credit Risk metrics - using ...
1 Opening(s)
4.0 Year(s) To 10.0 Year(s)
Not Disclosed by Recruiter
Responsibility:
Powertrain vehicle function concept development based on function benchmarking. New vehicle function model development & validation. Final spec development after detail DFMEA & Design reviews.
Technical Competencies:
Perform requirement engineering and function development of function such powertrain vehicle function and CNG software in ECU.
Perform function benchmarking suing actual vehicle and literature study.
Prepare ...
1 Opening(s)
2.0 Year(s) To 5.0 Year(s)
Not Disclosed by Recruiter
Scope of Work:
CuraTrail: Consumer-facing preventive health platform with HRV-based stress and readiness scoring (wearables and smart rings). Cross-platform mobile build using Flutter (Dart).
Siyan Reflect: AI-powered CBT coaching app on a Swift / WebSocket / Azure voice pipeline, with two-layer memory injection, mood check-ins, session summaries, and pattern intelligence. Hybrid frontier-API + open-source-model ...
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
2 Opening(s)
6.0 Year(s) To 10.0 Year(s)
0.00 LPA TO 32.00 LPA
Required Skillset:
6-10 years of experience in Risk Management with consulting firms or Banks and other Financial Services
Certifications like CFA, FRM, CQF
Proficiency in MS Excel and PowerPoint
Excellent knowledge of AI/ML techniques, including Python, R, and other relevant tools
Strong communication skills (oral, written, and email drafting skills)
Good organizational, analytical, problem-solving, and project ...
1 Opening(s)
2.0 Year(s) To 12.0 Year(s)
Not Disclosed by Recruiter
JD 1 : Quant Analyst – Market RiskRole Summary:The Market Risk Quant Analysts will focus on market risk model development, validation, andcompliance, ensuring that banks meet regulatory and risk management standards.Key Responsibilities: Validate market risk models, including Value-at-Risk (VaR), Expected Shortfall, and StressTesting frameworks. Develop and enhance models for FRTB ...