Senior Data Scientist

Senior Data Scientist
Opkey | Series B Funded | Noida, India (In-Office) | Full-Time The Opportunity
Opkey, a Series B funded enterprise application lifecycle management platform, is looking for a Senior Data Scientist to join our team in Noida. We need someone who can build predictive models, design machine learning algorithms, and extract insights that transform how enterprises manage Oracle Fusion, Workday, and SAP. Were not pitching a vision were scaling a reality. Our platform already processes hundreds of gigabytes of enterprise data. Now we need a scientist who can make that data predict the future. This is your chance to be part of building something that will define a category. About Us
Opkey is redefining how enterprises manage the lifecycle of their most critical applications. Weve built the platform that takes organizations from Design to Configure to Test to Train, powered by agentic AI. Our customers already include Fortune 500 companies and top global system integrators. They trust us with hundreds of gigabytes of their most sensitive enterprise data payroll files, configuration exports, test results because weve proven we can turn that data into intelligence they cant get anywhere else. Were already doing what others are only talking about. Our systems already compare millions of payroll records. Our platform already validates enterprise configurations at scale. Our AI already helps organizations manage application lifecycles that used to take armies of consultants. Now were scaling. And we need exceptional people to help us go from category creator to category leader. This is founder mode, not corporate mode. We move fast, we solve hard problems, and we ship things that matter. Why This Role Matters
Enterprise data is everywhere but insight is rare. Organizations have terabytes of payroll runs, configuration snapshots, and test results, but no way to know what it means or whats coming next. Weve built the infrastructure. Now we need the intelligence. Youll be the person who turns raw enterprise data into predictions, patterns, and actionable insights. When you build a model that predicts payroll errors before they happen, real people get paid correctly. When your algorithm identifies configuration risks, you prevent outages that would affect thousands. This is already happening at Opkey. Youll help us do it smarter, faster, and at a scale no one else has achieved. What Youll Do
Youll join a team thats already processing enterprise data at scale. Your job is to build the machine learning models and statistical algorithms that extract intelligence from that data: Build Predictive Models: Develop ML models that predict payroll discrepancies, configuration failures, and test regressions before they happen. Use techniques like regression, classification, anomaly detection, and time-series forecasting. Design Anomaly Detection Algorithms: Create statistical models that identify meaningful variances in massive datasets millions of payroll records, thousands of configuration parameters and distinguish signal from noise. Develop Machine Learning Pipelines: Build end-to-end ML pipelines from feature engineering to model training to production deployment. Own the full lifecycle not just notebooks, but deployed, monitored, production systems. Run Experiments & A/B Tests: Design and execute experiments to validate hypotheses, measure model performance, and continuously improve prediction accuracy. Extract Cross-Enterprise Insights: Apply clustering, pattern recognition, and statistical analysis to identify best practices, failure modes, and benchmarks across hundreds of implementations. Communicate Insights to Stakeholders: Translate complex model outputs into clear, actionable recommendations. Build visualizations and reports that help nontechnical users understand the data. Skills & Qualifications
Required Technical Skills
Python for Data Science: 4+ years of production experience with Python Pandas, NumPy, Scikit-learn, and either TensorFlow or PyTorch Machine Learning Expertise: Hands-on experience building and deploying ML models regression, classification, clustering, anomaly detection, time-series forecasting Statistical Analysis: Deep foundation in statistics hypothesis testing, probability distributions, A/B testing, regression analysis Feature Engineering: Ability to transform raw data into meaningful features that improve model performance SQL Proficiency: Comfortable writing complex queries to extract, transform, and analyze data from relational databases Model Deployment: Experience taking models from notebooks to production MLOps concepts, model monitoring, and performance tracking Nice to Have
Experience with deep learning and neural networks Background in natural language processing (NLP) Exposure to enterprise applications (Oracle, Workday, SAP) Experience with big data tools (Spark, Hadoop) for large-scale model training Knowledge of data visualization tools (Matplotlib, Seaborn, Plotly, Tableau) Mindset & Approach Hypothesis-Driven: You start with questions, not tools. You design experiments to test ideas and let data guide decisions. Production-Oriented: You understand that a model in a notebook has zero business value. Impact comes from deployed systems. Business Translator: You can explain what a model does and why it matters to non-technical stakeholders. Founder Mentality: You thrive in ambiguity, make decisions with incomplete information, and care about outcomes over process. Continuous Learner: ML is evolving fast. You stay current with new techniques and know when to apply them. What Were NOT Looking For
People who only want to build models but not deploy them Those who cant explain their work to non-technical audiences Anyone who needs perfect data before they can start (enterprise data is messy) Candidates who optimize for algorithmic elegance over business impact
What We Offer
Competitive salary + meaningful equity in a company thats already winning The chance to build ML systems that Fortune 500 companies depend on A team that values speed, ownership, and results over politics Direct impact your models will affect real enterprise operations The opportunity to be part of history building the intelligence layer that defines how enterprises manage their most critical applications Weve built the data infrastructure. Now we need someone to make it intelligent. Apply with your resume and a brief note about a predictive model youve built and deployed. Opkey is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.