Aeratechnology6mo ago

Senior Data Scientist

India·PuneFull-timesenior

Data ScienceData ScientistDataData & AI

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Overview

Aera Technology is the Decision Intelligence company. We deliver innovation and services that enable enterprises to operate sustainably, intelligently, and efficiently.

Technical Tools

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Aera Technology is the Decision Intelligence company. We deliver innovation and services that enable enterprises to operate sustainably, intelligently, and efficiently. Our platform, Aera Decision Cloud™, integrates with your existing systems to digitize, augment, and automate decisions in real time. Aera helps enterprises around the world transform decision making – delivering millions of recommendations that have resulted in significant revenue gains and cost savings for some of the world’s best-known brands.

We are seeking a Senior Data Scientist to drive the successful implementation of high-impact ML solutions for our enterprise customers. This is a critical role focused squarely on solving complex customer problems by applying advanced Data Science techniques during implementation projects. You will be expected to rapidly understand, analyze, and diagnose client-specific issues, providing quick, robust analytical insights and technical resolutions. While your focus is on customer implementation delivery and support, you will serve as a key feedback loop, working closely with the internal Data Science Product team to influence future tooling and features.

Data Science Customer Success & Problem Solving: Act as the senior technical point of contact, driving successful outcomes by identifying, scoping, and leading data science projects that directly address high-value customer problems. Measure and report on the business impact (ROI, efficiency gains) of deployed models. Ensure rigorous testing and validation of all new data science features and model deployments.

Technical Design & Implementation: Design, implement, monitor, and maintain scalable, production-grade Data Science systems. Research and evaluate the latest in Machine Learning, Generative AI, and advanced statistical models for new feature development. Actively scout, evaluate, and implement the latest advancements in Data Science, Machine Learning (MLOps, LLMs/Generative AI), and AI to maintain Aera’s technical edge.

Data Science Technical Support: Take ownership of critical model performance issues. You will champion rapid resolution for Data Science models and pipelines, working collaboratively with Support, Customer Success, and Product teams to implement robust, long-term technical solutions.

Product Collaboration: Act as a technical advisor to the Product Team by sharing insights from field implementations. You will provide data-driven feedback on model performance and usability to help inform future improvements to Aera Decision Cloud’s Data Science capabilities.

We are looking for a hands-on practitioner—someone who is deeply technical, customer-focused, and passionate about engineering excellence.

Customer Focus: You are someone who is obsessed about solving customer problems and delivering tangible business value using Data Science, understanding the criticality of timely resolution and deployment.

Technical Foundation: Master’s or Bachelor’s Degree in Computer Science, Engineering, Mathematics, Statistics, or a related quantitative field with a focus on Data Science/Machine Learning/Deep Learning/AI.

Strong grounding in core ML concepts—bias-variance tradeoffs, feature engineering, model evaluation, uncertainty quantification—not just framework/API familiarity.

Experience: 7+ years of experience as a Data Scientist or Machine Learning Engineer, ideally in a B2B SaaS or product development setting.

Modern ML/AI Expertise: Proven, hands-on experience designing, developing, and deploying systems utilizing the latest advancements in AI (e.g., MLOps practices, Generative AI, vector databases, or transformer models).

Production Deployment: Strong experience with the full ML lifecycle, including translating research models into scalable, production-ready services using modern software development practices.

Technical Communication: Ability to distill complex Data Science concepts into clear, actionable insights for product managers, customer executives, and cross-functional teams.

Technical Stack:

Exceptional proficiency in SQL and Python; able to write high-quality, high-performance, and maintainable code.

Experience with distributed systems and ML frameworks such as Dask, Ray, or Spark.

Familiarity with production ML services like Kubeflow, Sagemaker, or similar cloud-native MLOps tools is a significant advantage.