How often are new jobs added?

Every minute. We scan thousands of hiring sources in real-time so you see roles as soon as they go live, often hours before they appear on public job boards.Early access = higher odds of getting interviewed.

Why can I only view limited per day on the free plan?

Free access gives everyone a fair starting point. But seeing every job instantly creates an unfair advantage, so unlimited browsing is reserved for Pro users who want full access to fresh, hidden, and time-sensitive roles. Limiting free browsing also prevents automated scraping by competitors.

What sources do you pull jobs from?

We aggregate from: - company career pages - startup platforms - ATS systems (Greenhouse, Lever, Ashby, Workable, etc.) - niche regional job boards - hidden talent networks not indexed by Google Over 50,000 sources → one unified feed.

Are these jobs legitimate?

Yes. We automatically remove: - expired listings - spam - shady postings - duplicates - fake "ghost jobs" Every job you see is active, real, and verified at the source.

What’s the benefit of upgrading to Pro?

Pro gives you an information advantage. You unlock: - unlimited job browsing - real-time alerts for your saved filters - early access to newly discovered roles - deeper filtering (salary, remote, visa, experience, etc.) - access to hidden sources most job seekers never find Pro users consistently apply earlier and get significantly higher interview rates.

Can I filter by location, experience, remote, or salary?

Yes and Pro unlocks the power filters job boards don’t show you, including: - roles posted in the last 24 hours - company ATS only - startup-only sources - remote-flex categories - international roles by timezone

Why are early alerts so important?

Most job applications pile up within the first 6–12 hours after posting. If you apply early, you skip the crowd and rank higher in recruiter screening. Our alerts give you that timing advantage.

If the employer provides it, yes. If not, we attempt to estimate using salary bands from public and private datasets (Pro only).

Is DayOneJobs suitable for senior roles too?

Yes. We cover all roles, from internships to senior-level. Filters simply let you tailor your feed to your level.

JOB DETAILS

Junior Data Scientist

CompanyDigitap.ai

LocationBengaluru

Work ModeOn Site

PostedMay 24, 2026

About The Company

DIGITAP provides high tech advanced AI/ML solutions to new age internet driven businesses for reliable, fast and 100% compliant Customer Onboarding, Automated Risk Management along with Big Data enabled services like Risk Analytics and Customized Scorecards. Our proprietary Machine Learning Algorithms and Modules provide one of the best success rates in the market. Our Services includes; 1. LOS and Customer Onboarding Suite 2. Employment & Income Verification 3. Account Aggregator Solutions 4. Alternate Data Based Risk Management Suite 5. Expense Manager 6. Digi - KYC 7. Digilocker 8. Digi Sign & Digi - Nach All the solutions are accessible in the form of easy to integrate APIs. Visit us to know more!

About the Role

About Digitap.ai: DIGITAP.AI is an Enterprise SaaS company providing high-tech advanced AI/ML, Alternate Data Solutions to new-age internet-driven businesses for reliable, fast, and 100% compliant Customer Onboarding, Alternate Data Solutions for Automated Risk Management, and other Value-Added Services. Our proprietary Machine Learning Algorithms and Modules provide one of the best success rates in the market. We work with the top digital lenders of India & the team brings together deep and vibrant experience in Fintech Product & Risk Management, Fraud Detection, and Risk Analytics. Culture and Benefits: <ul><li>Innovative Start-up Environment: Enjoy the flexibility to design, implement, and influence the development of cutting-edge solutions.</li><li>Transparency and Meritocracy: We value clear communication, eschew politics, and promote an open culture where contributions are recognized and rewarded.</li><li>Ownership and Impact: We encourage team members to take ownership, think beyond their roles, and contribute to the company's success in meaningful ways.</li><li>Competitive Compensation: We offer a competitive salary and a potential equity package, aligning your success with the company's growth.</li></ul><div style="box-sizing: border-box; outline: 0px; color: rgb(0, 0, 0); font-family: -apple-system, BlinkMacSystemFont, ;"><h4 style="box-sizing: border-box; outline: 0px; font-family: -apple-system, BlinkMacSystemFont, ;">Job Description:</h4></div><div>Key Responsibilities<span style="box-sizing: inherit; margin: 0px; padding: 0px; border-color: rgba(0, 0, 0, 0.9); border-style: none; border-width: 0px; border-image: none 100% / 1 / 0 stretch; font-size: 14px; vertical-align: baseline; background-image: none; background-position: 0% 0%; background-size: auto; background-repeat: repeat; background-attachment: scroll; background-origin: padding-box; background-clip: border-box; outline: rgba(0, 0, 0, 0.9) none 0px; font-family: -apple-system, system-ui, BlinkMacSystemFont, "> <ul><li>Assist in developing machine learning models for credit scoring, fraud detection, and risk prediction</li><li>Work with large datasets for data cleaning, preprocessing, and feature engineering</li><li>Support model experimentation, evaluation, and performance optimization</li><li>Contribute to building automated ML pipelines for data processing and model training</li><li>Monitor model performance and data drift in production systems</li><li>Collaborate with data scientists, engineers, and product teams to translate business problems into ML solutions</li></ul></div><div>Required Skills</div><ul><li>1+ year experience working with Machine Learning models (classification/regression)</li><li>Strong Python programming skills</li><li>Experience with NumPy, Pandas, Scikit-learn, Matplotlib/Seaborn</li><li>Knowledge of model evaluation, cross-validation, overfitting, and feature importance</li><li>Experience with data cleaning, preprocessing, and feature engineering</li><li>Basic SQL querying skills</li><li>Familiarity with Git and collaborative development</li></ul><div>Preferred Qualifications<span style="box-sizing: inherit; margin: 0px; padding: 0px; border-color: rgba(0, 0, 0, 0.9); border-style: none; border-width: 0px; border-image: none 100% / 1 / 0 stretch; font-size: 14px; vertical-align: baseline; background-image: none; background-position: 0% 0%; background-size: auto; background-repeat: repeat; background-attachment: scroll; background-origin: padding-box; background-clip: border-box; outline: rgba(0, 0, 0, 0.9) none 0px; font-family: -apple-system, system-ui, BlinkMacSystemFont, "> <ul><li>Degree in Computer Science, Data Science, Mathematics, or related field</li><li>Exposure to Fintech / Credit Risk / Business Analytics</li><li>Basic understanding of MLOps, model deployment, or pipeline automation</li><li>Passion for learning new ML tools and technologies</li></ul></div><div> </div>

Key Skills

Machine LearningPythonNumPyPandasScikit-learnMatplotlibSeabornModel EvaluationCross-validationOverfittingFeature EngineeringSQLGit