Staff Data Scientist

We’re looking for a **Staff Data Scientist** to advance the future of Construction Intelligence. As a member of our **AI Studio team**, you’ll help deliver the future of our next-generation insights, recommendations, and automated experience roadmaps, and to enable AI capabilities to everyone in construction on a global platform.

The construction vertical is ripe for technological innovation. Construction impacts the lives of nearly everyone in the world, and yet it’s one of the least digitized industries. Procore is leading the market with our SaaS construction platform. We build for real people with real experiences, empowering Groundbreakers to develop and transform the communities where we all live.

This position will report to the Director of Machine Learning and has the opportunity to work from our Bangalore or Pune office. We’re looking for someone to join our team immediately.

**What you’ll do**:

- Work with large scale structured and unstructured data, design and conduct experiments, and analyze and interpret results for Procore product, business and operational use cases.
- Work collaboratively with cross-functional partners including software engineers, product managers, operations and data scientists, identify opportunities for business impact, understand, refine, and prioritize requirements for machine learning models, drive engineering decisions, and quantify impact.
- Leverage third-party and in-house Data Science tools, such as Jupyter Notebooks, to develop reusable, enable fast model development, low-latency serving and ease of model quality upkeep. Example projects include: feature platform, model interpretability, hyperparameter optimization, concept drift detection.
- Lead and mentor junior data scientists, provide technical guidance and code reviews, and foster a culture of collaboration and innovation.
- Conduct research on the latest Data Scientist and Machine Learning trends and techniques, and publish papers and patents as appropriate.

**Who we’re looking for**:

- 8+ years of industry experience in applied Machine Learning.
- Exceptional written and verbal communication skills
- Strong programming (Python / Java / C++ or equivalent) and data engineering skills
- Strong understanding in the machine learning and data science technical ecosystems (e.g., Tensorflow, Pytorch, MLflow, Snowflake, SageMaker, Scikit, etc)
- Deep understanding of Machine Learning best practices (eg. training/serving skew minimization, A/B test, feature engineering, feature/model selection), algorithms (eg. gradient boosted trees, neural networks/deep learning, optimization) and domains (eg. natural language processing, computer vision, personalization and recommendation, anomaly detection)
- Understand cost of software development / tech debt and long-term maintenance
- Passion for customers and seeking a deep understanding of end-user problems as well as competitive and market trends in the AI space
- Experience in leading and managing Data Science projects and teams, and delivering high-quality results in a fast-paced environment

**Additional Information**

**Perks & Benefits**

At Procore, we invest in our employees and provide a full range of benefits and perks to help you grow and thrive. From generous paid time off and healthcare coverage to career enrichment and development programs, learn more details about what we offer and how we empower you to be your best.

**About Us**

Procore Technologies is building the software that builds the world. We provide cloud-based construction management software that helps clients more efficiently build skyscrapers, hospitals, retail centers, airports, housing complexes, and more. At Procore, we have worked hard to create and maintain a culture where you can own your work and are encouraged and given resources to try new ideas. Check us out on Glassdoor to see what others are saying about working at Procore.

We are an equal-opportunity employer and welcome builders of all backgrounds. We thrive in a diverse, dynamic, and inclusive environment. We do not tolerate discrimination against employees on the basis of age, color, disability, gender, gender identity or expression, marital status, national origin, political affiliation, race, religion, sexual orientation, veteran status, or any other classification protected by law.

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