Jump Cloud

Senior Data Scientist - India

Job Description

About the Role

As a Senior Data Scientist at JumpCloud, you will be a key leader in our mission to turn complex data into competitive intelligence and automated solutions. You’ll be joining a high-impact team where you will do more than just analyze data, but designing the predictive models and machine learning frameworks that power our most critical business decisions across all business units (Finance, Marketing, Sales, Growth, UX, Customer Success, Product).

In this role, you will lead the end-to-end lifecycle of data science projects, from initial research and experimental design to deploying scalable models in production. You will act as a strategic partner to our product and business teams, translating high-level challenges into technical roadmaps. As a senior member of the team, you will also play a vital role in mentoring our analysts and scientists, fostering a culture of technical excellence, and ensuring our data practices stay ahead of industry trends.


What you’ll be doing:
  • Collaborating and driving large, impactful projects involving predictive modeling, advanced statistical analysis, and machine learning integration with involvement across various stakeholders, business units, and technical partners.
  • Owning the outcomes of the data science initiatives you’re leading. You’re not just building models; you hold yourself responsible for the performance, accuracy, and real-world business impact of the algorithmic solutions you deploy.
  • Gathering requirements and providing actionable, data-driven recommendations to business stakeholders that are seen routinely at an executive level, driving the adoption of automated decision-making and predictive insights.
  • Mentoring and growing the other data scientists and analysts in the company. We’ve got a great team full of potential; you’ll be helping other members master advanced techniques, improve their coding standards, and achieve their full technical potential.
  • Supporting the team’s research roadmap, strategic technical decision-making, and long-term data strategy planning, ensuring our infrastructure supports the future of our modeling needs.
  • Staying up-to-date on industry trends, emerging AI technologies (such as LLMs and Generative AI), and best practices in MLOps, and applying them to solve our most complex business challenges.

    • We’re looking for:
  • 5+ years of hands-on experience in data science or machine learning, with a proven track record of deploying models that drove measurable business impact, SaaS industry preferred.
  • Advanced quantitative and modeling experience (Regression, Clustering, NLP, etc.). Experience working with LLMs, including prompt engineering and leveraging APIs.
  • Advanced predictive modeling skills and a passion for data storytelling and translating complex algorithmic outputs into business strategy.
  • Proficiency in machine learning frameworks (Scikit-learn, XGBoost, PyTorch, or TensorFlow); experience with MLOps and model deployment highly preferred.
  • Strong mentoring skills, with a track record of leveling up the technical capabilities of a data team.
  • Advanced knowledge and experience in SQL and relational databases; Snowflake experience highly preferred.
  • Expertise in scripting languages such as Python (Jupyter, Pandas, Numpy, Scikit-learn) and/or R (tidyverse, tidymodels) to build scalable data products.
  • Strong attention to detail and a desire to stay at the forefront of AI/ML research.
  • Strong “owner” mindset to take ambiguous business problems and turn it into a concrete and actionable project.
  • Effective stakeholder management and communication skills, specifically the ability to explain complex AI/ML concepts to non-technical partners.
  • Effective project management and organizational skills.
  • Experience supporting and working with cross-functional teams in a fast-paced, unstructured, dynamic environment.
  • Bachelor's degree (or equivalent experience) in Computer Science, Statistics, Informatics, Information Systems, or another quantitative field.

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