AI-Powered FinOps & Product Analytics Engineer

AI-Powered FinOps & Product Analytics Engineer

Full-Time 63000 - 77000 £ / year (est.) On-site
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At a Glance

  • Tasks: Build AI-powered tools and data models for operational insights across teams.
  • Company: Join Intapp, a forward-thinking company in the tech industry.
  • Benefits: Enjoy competitive pay, flexible work options, and growth opportunities.
  • Other info: Be part of a dynamic team with a focus on innovation.
  • Why this job: Make an impact by shaping data solutions in a greenfield environment.
  • Qualifications: Strong skills in SQL, Python, and analytical databases required.

The predicted salary is between 63000 - 77000 £ per year.

Intapp is seeking a curious Fin Ops & Product Analytics Engineer to join the Dev Ops & Cloud Platform team.

You will build the data foundation and AI-powered tooling delivering operational insights for engineering, product, and finance stakeholders across Intapp.

You will design data models, build ingestion pipelines, and develop AI-powered reporting while ensuring reliability and scale in a greenfield environment.

Strong SQL, Python, and experience with analytical databases are essential.

AI-Powered FinOps & Product Analytics Engineer employer: Intapp

At Intapp, we pride ourselves on being an exceptional employer, offering a dynamic work environment in Belfast that fosters professional growth and collaboration. Our commitment to employee development is evident through comprehensive training opportunities, flexible working arrangements, and a culture that values creativity and teamwork. With a focus on well-being and community support, we ensure our team members thrive both personally and professionally while making a meaningful impact within the organisation.

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Contact Details:

Intapp Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land AI-Powered FinOps & Product Analytics Engineer

✨Get Involved in Data Science Meetups

Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Intapp!

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✨Apply Directly through Our Website

When you find a suitable opening like AI-Powered FinOps & Product Analytics Engineer at Intapp, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!

We think you need these skills to ace AI-Powered FinOps & Product Analytics Engineer

SQL
Python
Data Modelling
Data Ingestion Pipelines
AI-Powered Reporting
Analytical Databases
Operational Insights

Some tips for your application 🫡

Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!

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Craft a Tailored Cover Letter:For a full-time role at Intapp, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.

Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Intapp. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!

How to prepare for a job interview at Intapp

✨Brush Up on Your Statistics

For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!

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✨Get Comfortable with Python and R

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✨Prepare for Case Studies

Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.