Qureos Mentor

Digitap.AI Enterprise Solutions

<div><div><h4 class="jobSectionHeader"><b>About Us:</b></h4><div>
DIGITAP.AI is a cutting-edge provider of AI/ML solutions tailored for the modern, internet-driven business landscape. Our advanced technologies empower businesses with reliable, fast, and fully compliant customer onboarding, automated risk management, and big data-enabled services, including Risk Analytics and Customised Scorecards.</div><div></div><div><br>
Our proprietary machine learning algorithms and modules boast some of the highest success rates in the market. Partnering with the largest digital lenders in India, our team is a vibrant mix of expertise in Fintech Product &amp; Risk Management, Fraud Detection, and Big Data Analytics.<br>
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<b>Culture and Benefits:</b></div><div><b><br>
Innovative Start-up Environment:</b> Enjoy the flexibility to design, implement, and influence the development of cutting-edge solutions.</div><div><b><br>
Transparency and Meritocracy:</b> We value clear communication, eschew politics, and promote an open culture where contributions are recognized and rewarded.</div><div><b><br>
Ownership and Impact:</b> We encourage team members to take ownership, think beyond their roles, and contribute to the company's success in meaningful ways.</div><div><b><br>
Competitive Compensation</b>: We offer a competitive salary and a potential equity package, aligning your success with the company's growth.</div><div></div><h4 class="jobSectionHeader"><b><br>
Job Description:</b></h4><div>
As a <b>Data Scientist &ndash; Machine Learning</b>, you will design and develop advanced ML models for credit scoring and risk assessment, while also leading research and innovation in large-scale transformer-based systems.</div><div></div><h4 class="jobSectionHeader"><b><br>
Key Responsibilities:</b></h4><p><b>
Credit &amp; Risk Analytics</b>: Design, develop, and optimize ML models for credit scoring, risk prediction, and scorecard generation.</p><div><b><br>
Model Deployment &amp; Automation:</b> Implement scalable pipelines for model training, validation, and deployment in production environments.</div><div><b><br>
Feature Engineering:</b> Identify, extract, and engineer key features from structured and unstructured data to enhance model performance.</div><div><b><br>
Model Monitoring</b>: Establish continuous monitoring frameworks to track model drift, performance metrics, and data quality.</div><div><b><br>
Research &amp; Innovation:</b> Explore and apply state-of-the-art ML and transformer architectures to improve predictive accuracy and interpretability.</div><p><b><br>
Collaboration:</b> Work closely with data engineers, product managers, and domain experts to translate business objectives into robust ML solutions<b>.</b></p><h4 class="jobSectionHeader"><b><br>
Required Skills and Experience:</b></h4><p><b>
Machine Learning:</b> 2+ years of hands-on experience in developing, training, and deploying ML models for structured or tabular data.</p><div><b><br>
Statistical Modeling:</b> Solid understanding of statistical concepts, feature engineering, and model evaluation techniques.</div><div><b><br>
ML Frameworks:</b> Experience with <b>scikit-learn</b>, <b>PyTorch</b>, or <b>TensorFlow</b> for building and optimizing predictive models.</div><div><b><br>
Python Programming:</b> Strong proficiency in <b>Python</b>, with experience using <b>NumPy</b>, <b>Pandas</b>, and <b>Matplotlib</b> for data manipulation and analysis.</div><div><b><br>
Data Handling:</b> Practical experience with large datasets, data cleaning, preprocessing, and transformation for ML workflows.</div><div><b><br>
SQL &amp; APIs:</b> Proficiency in writing <b>SQL queries</b> and integrating ML models with <b>APIs</b> or backend systems.</div><div><b><br>
Version Control &amp; Collaboration:</b> Familiarity with <b>Git</b> and collaborative model development practices.</div><p><b><br>
Analytical Thinking:</b> Strong problem-solving skills with the ability to translate business problems into data-driven ML solutions.</p><div></div><h4 class="jobSectionHeader"><b><br>
Preferred Qualifications:</b></h4><p><b>
Education:</b> Bachelor&rsquo;s or Master&rsquo;s degree in <b>Computer Science</b>, <b>Data Science</b>, <b>Mathematics</b>, or a related quantitative field.</p><div><b><br>
Experience:</b> Min2 years of experience in <b>machine learning</b>, <b>data analytics</b>, or <b>applied statistics</b> roles.</div><div><b><br>
Cloud Platforms:</b> Exposure to <b>AWS</b>, <b>GCP</b>, or <b>Azure</b> for model deployment or data processing.</div><div><b><br>
Domain Knowledge:</b> Familiarity with <b>fintech</b>, <b>credit risk</b>, or <b>business analytics</b> domains.</div><div><b><br>
Automation &amp; MLOps:</b> Basic understanding of <b>model deployment</b>, <b>monitoring</b>, or <b>pipeline automation</b> tools.</div><p><b><br>
Continuous Learning:</b> Enthusiasm for exploring new ML algorithms, open-source tools, and emerging technologies in data science.</p></div></div><p></p>

Data Scientist ML Engineer

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Digitap.AI Enterprise Solutions

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Data Scientist ML Engineer