403 Data Science Roles jobs in Delhi
ICT Expert/ Data Analysis Expert
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ICT Expert /Data Analysis :-
Common functions:
i. To assist the Network Planning Group (NPG) on the matters related to PM Gati Shakti and National Logistics Policy (NLP).
ii. To provide expertise for integration of interconnected multimodal network transport and infrastructure for efficient movement of people, Goods and services.
iii Assist in improving decision making through effective logistics data analytics, standardizations through streamlining of processes
iv. Assessment of project proposals included in the PM Gati Shakti National Master Plan in consultation
with other domain specific SMEs, Officers of TSU, Logistics Division and Line Ministries/Departments.
v. Examination/ evaluation of projects on PM Gati Shakti principles like logistics efficiency, utility to economic clusters, integrated approach to planning, perspective of multimodality and area development approach.
vi. Having knowledge/aware of Government policies, regulations and best practices, principles to the extent relevant to the Subject matter/PM Gati Shakti/National Logistics Policy with a focus on sustainable and inclusive development principles.
vii. Preparation of reports, presentations, and other communication materials to convey landings,
recommendations and implementation strategies and play role in capacity building.
viii. Knowledge for use of project management tools and techniques, as well as digital technologies such
as GlS, Transportation modelling softvvare etc. during evaluation of project proposals.
ix. Economic Nodes are important for critical evaluation of infrastructure projects. Accordingly basic understanding of economic nodes i.e. SEZ, CFS, lCDs, industrial nodes, Export Oriented Districts etc. is desirable.
xi. Any other work related to PM Gatishakti, Network Planning Group, National Logistics Policy in
particular and Logistics Sector in general.
x. To collaborate with government agencies, prlvate sector partners, and international organizations to develop innovative solutions for critical gaps in integrated planning.
Expert Assessment of all project proposals included in the PM Gati Shakti NMP in consultation with other domain specific SMEs and Directors in Technical Support Unit (TSU) and Logistics Division as well as with respective Line Ministries from the purview of synchronization of efforts
Undertaking interaction with users, Central/ State Government, and other stakeholders to identify gap areas
- Assessment of LEADS and sectoral reports for identification of gap Coordination for development of lT tools for decision support
- Assistance in appraisal/identification of telecom connectivity projects
- To coordinate for maintenance of ICT systems with Logistics Division interaction with BISAG-N for mapping of projects/new projects
- Development of data analytics for decision support
- Coordination for development of lT tools for decision support
- Coordination w.r.t. data collection, updating and storage/ Maintenance
- Preparation of Monthly analytical reports on TSU functioning Monitoring and tracking of action points identified in EGoS and NPG meetings, lnter-Ministerial Meetings and Meetings with State Governments
- Generate customized reports as per compliance requirement for Parliament / PMO/Cabinet Secretariat/ Office of C&lM, etc
Freelancer - Python with Data analysis
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We are looking for freelancers experienced in Python with strong expertise in Statistics or Data Analysis.
skills include: Python (Pandas, NumPy, SciPy, Scikit-learn), R, SQL, Statistical Modeling, Hypothesis Testing, Regression, Classification.
Freelance Statistical Researcher – Demographic & Population Modeling
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Duration: 2-Month Contract (Renewable)
Compensation: ₹0,000/month (net, based on deliverables)
We are seeking a highly qualified freelance statistician to explore and analyze publicly available demographic datasets—including respondent-level microdata where available—and translate them into actionable statistical insights. The ultimate goal is to develop frameworks and schemas for generating synthetic populations of various Indian states.
This project is ideal for a candidate passionate about data exploration, sampling theory, and synthetic data generation for policy, market, or simulation purposes.
Key Responsibilities
- Data Exploration & Cleaning
- Locate, access, and curate publicly available demographic datasets (census, NFHS, WVS, ASER, NSSO, etc.).
- Conduct thorough quality checks and handle missing or inconsistent data.
- Statistical Analysis & Modeling
- Perform distribution analysis, parameter estimation, and relationship mapping between demographic variables.
- Apply sampling techniques to design representative synthetic populations.
- Identify key demographic and behavioral parameters that inform population modeling.
- Schema & Synthetic Population Development
- Build statistical frameworks and schemas to simulate respondent-level data for Indian states.
- Develop replicable workflows and documentation for ongoing data updates.
- Reporting & Communication
- Present findings in clear, visualized formats (tables, charts, dashboards).
- Recommend refinements to improve the representativeness and robustness of the synthetic population models.
Required Qualifications
- Education: Master’s degree or higher in Statistics, Econometrics, Data Science, or Quantitative Social Sciences from a premier institute (ISI, IITs, IISc, Delhi School of Economics, etc.).
- Core Expertise:
- Advanced understanding of sampling theory and experimental design.
- Strong proficiency in statistical programming (R, Python, or Stata).
- Knowledge of Bayesian inference and synthetic data generation techniques is a plus.
- Experience:
- Prior work with large demographic or respondent-level datasets.
- Track record of producing actionable statistical insights.
Key Skills
- Distribution and parameter analysis
- Survey sampling & weighting
- Regression and multivariate modeling
- Data wrangling and cleaning
- Reproducible workflow creation (scripts, notebooks)
- Clear presentation of statistical findings
Compensation & Engagement
- Fixed monthly fee of ₹50,00 NR.
- Flexible, output-oriented schedule.
- Initial engagement for 3 months with potential for extension based on performance.
Machine Learning
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Role & Mission
As our Machine Learning / LLM Orchestrator, you won't just build code faster—you'll architect the AI frameworks that empower every team member to build and deploy AI‑driven features independently. You will design, fine‑tune and deploy large language models (LLMs), create internal tools that allow product managers and engineers to generate front‑end and back‑end components with minimal friction, and scale adaptive fraud‑risk models for real‑time transactions.
Key Responsibilities
- Build and fine‑tune local LLM engines; design automated pipelines for code generation, testing, documentation and deployment.
- Architect microservices and APIs that integrate AI models into our payment gateway, risk‑management systems and new product features.
- Develop adaptive machine‑learning models for transaction monitoring and fraud‑risk management.
- Create internal AI toolkits and frameworks enabling non‑engineers to develop UI/UX, backend services and ML workflows aligned with existing architecture.
- Establish best practices for prompt engineering, model evaluation and agent orchestration; mentor engineers and product teams.
- Collaborate with leadership to shape our AI strategy and roadmap.
Qualifications
- 7–8 years of software engineering experience (backend or full‑stack); fintech or payments exposure is a plus.
- At least 2 years building, fine‑tuning or deploying LLMs or custom ML models.
- Proficiency with PyTorch or TensorFlow, and familiarity with orchestration frameworks (e.g. LangChain, LlamaIndex).
- Experience with CI/CD pipelines, Docker/Kubernetes and microservices.
- Demonstrated ability to deliver production‑ready AI solutions quickly and iteratively.
- Strong communication skills and a passion for empowering others through technology.
Why Join Us?
- Shape the future of AI‑native fintech—your work will directly influence how our company harnesses AI at scale.
- High autonomy and ownership; you'll define our AI frameworks and standards.
- Fast‑paced, experimentation‑first environment that values innovation and learning.
- Competitive compensation and flexible remote/hybrid working options.
About Company
SabPaisa (SRS Live Technologies) is an RBI Authorised Payment Aggregator.
Founded in 2016 with headquarters in New Delhi, a corporate office in Kolkata, and regional offices across the country, it is a rapidly advancing fintech company. SabPaisa is dedicated to providing simplified payment solutions, offering customizable options tailored to the client's unique needs.
How Are We Different
SabPaisa's dynamic, PCI-DSS and SSL-certified payment gateway offers secure online checkout with diverse options—Cards, Net-Banking, UPI, Wallets, and offline choices like e-Cash, e-NEFT & Bharat QR, available at nearly 10 Lac Cash Counters nationwide.
Our white-labelled payments and collection suite partners with banks like BOI, BOB, IDFC First, Canara, UBI & Indian Bank, processing over INR 94.9 billion.
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Senior Data Scientist - Machine Learning
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Key Responsibilities:
- Design, develop, and implement advanced machine learning models and algorithms to address challenging business and research problems.
- Clean, process, and transform large, complex datasets from various sources to prepare them for analysis and model training.
- Perform exploratory data analysis (EDA) to identify patterns, trends, and insights that can inform model development.
- Evaluate and optimize the performance of machine learning models using appropriate metrics and validation techniques.
- Deploy machine learning models into production environments, working closely with engineering and software development teams.
- Conduct rigorous A/B testing and experiments to validate model effectiveness and impact.
- Stay current with the latest advancements in machine learning, artificial intelligence, and data science research.
- Communicate complex technical findings and recommendations effectively to both technical and non-technical stakeholders.
- Mentor junior data scientists and contribute to the team's technical growth and knowledge sharing.
- Collaborate with cross-functional teams to define project scope, objectives, and deliverables.
- Master's or Ph.D. in Computer Science, Statistics, Mathematics, Physics, or a related quantitative field.
- Minimum of 5-7 years of hands-on experience as a Data Scientist or Machine Learning Engineer.
- Deep understanding of statistical modeling, machine learning algorithms (e.g., regression, classification, clustering, deep learning), and their applications.
- Proficiency in programming languages such as Python (with libraries like TensorFlow, PyTorch, Scikit-learn, Pandas, NumPy) or R.
- Experience with big data technologies (e.g., Spark, Hadoop) and cloud platforms (e.g., AWS, Azure, GCP) is highly desirable.
- Strong data visualization and storytelling skills.
- Excellent problem-solving, analytical, and critical thinking abilities.
- Ability to work independently and lead complex projects in a remote setting.
- Strong communication and collaboration skills.
- Experience in areas like natural language processing (NLP), computer vision, or reinforcement learning is a plus.
Data Scientist - Machine Learning Specialist
Posted 1 day ago
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Responsibilities:
- Develop, train, and deploy machine learning models for prediction, classification, and clustering.
- Perform in-depth data analysis, feature selection, and engineering to improve model performance.
- Design and execute A/B tests and other experiments to evaluate model effectiveness.
- Collaborate with cross-functional teams to define project requirements and deliver data-driven insights.
- Communicate complex findings and model results to technical and non-technical stakeholders.
- Stay current with the latest advancements in machine learning and data science research.
- Contribute to the development of data pipelines and analytics infrastructure.
- Ensure the quality, integrity, and reliability of data used for analysis.
Qualifications:
- Master's or Ph.D. in Data Science, Computer Science, Statistics, or a related quantitative field.
- Proven experience in applying machine learning techniques to real-world problems.
- Strong programming skills in Python or R, with extensive use of libraries like NumPy, Pandas, Scikit-learn, TensorFlow, or PyTorch.
- Solid understanding of statistical modeling, experimental design, and data mining techniques.
- Experience with data visualization tools and techniques.
- Familiarity with SQL and NoSQL databases.
- Excellent analytical, problem-solving, and communication skills.
- Experience with cloud platforms (AWS, Azure, GCP) and big data technologies is a plus.
Senior Data Scientist - Machine Learning
Posted 3 days ago
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Responsibilities:
- Design, develop, and implement machine learning models to address complex business problems, such as predictive analytics, recommendation systems, anomaly detection, and natural language processing.
- Extract, clean, and transform large, complex datasets from various sources to prepare them for analysis.
- Perform exploratory data analysis to identify patterns, trends, and insights.
- Evaluate and select appropriate algorithms and techniques for specific modeling tasks.
- Develop and deploy machine learning models into production environments.
- Monitor model performance in production and implement necessary improvements or retraining.
- Collaborate with software engineers to integrate ML models into existing products and services.
- Communicate complex technical findings and recommendations to both technical and non-technical stakeholders through clear visualizations and presentations.
- Stay current with the latest advancements in machine learning, artificial intelligence, and data science research.
- Mentor junior data scientists and contribute to the team's knowledge base.
- Contribute to the development of data infrastructure and best practices.
- Design and conduct A/B tests to measure the impact of implemented models.
- Master's or Ph.D. in Computer Science, Statistics, Mathematics, Physics, or a related quantitative field.
- Minimum of 5 years of experience as a Data Scientist, with a strong focus on machine learning applications.
- Proven experience in developing and deploying machine learning models in production using languages like Python or R.
- Proficiency with machine learning libraries and frameworks such as TensorFlow, PyTorch, scikit-learn, Keras, etc.
- Strong understanding of statistical modeling, probability, and hypothesis testing.
- Experience with data manipulation and querying tools, including SQL and big data technologies (e.g., Spark, Hadoop).
- Excellent data visualization skills (e.g., Matplotlib, Seaborn, Tableau).
- Strong analytical and problem-solving abilities.
- Excellent written and verbal communication skills, with the ability to explain complex concepts clearly.
- Demonstrated ability to work independently and collaboratively in a remote team environment.
- Experience with cloud platforms (AWS, Azure, GCP) is a plus.
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Lead Data Scientist - Machine Learning
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Machine Learning Engineer
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Machine Learning Engineer
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Job Title: H&E Image Analysis Scientist / Machine Learning Engineer- Spatial Omics (PhD)
Experience: Freshers
Location: Delhi
Job Description:
We are seeking a motivated PhD candidate interested in machine learning for histopathology
image analysis. The candidate will contribute to developing and optimizing deep learning
models to analyze digitized H&E slides for cancer classification and spatial mapping. This
role is well-suited for researchers aiming to apply advanced computational methods to
biomedical challenges.
Responsibilities:
● Design, develop, and train convolutional neural networks (CNNs) and related ML
models on H&E-stained histology images.
● Use and extend tools such as QuPath for cell annotations, segmentation models, and
dataset curation.
● Preprocess, annotate, and manage large image datasets to support model training
and validation.
● Collaborate with cross-disciplinary teams to integrate image-based predictions with
molecular and clinical data.
● Analyze model performance and contribute to improving accuracy, efficiency, and
robustness.
● Document research findings and contribute to publications in peer-reviewed journals.
Qualifications:
● PhD in Computer Science, Biomedical Engineering, Data Science, Computational
Biology, or a related discipline.
● Demonstrated research experience in machine learning, deep learning, or biomedical
image analysis (e.g., publications, thesis projects, or conference presentations).
● Strong programming skills in Python and experience with ML frameworks such as
TensorFlow or PyTorch.
● Familiarity with digital pathology workflows, image preprocessing/augmentation, and
annotation tools.
● Ability to work collaboratively in a multidisciplinary research environment.
Preferred:
● Background in cancer histopathology or biomedical image analysis.
● Knowledge of multimodal data integration, including spatial transcriptomics.