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Senior Data Scientist with AI product mindset

Pay
Pay not listed
Work setting
On-site — work setting source
Work setup in the employer’s posting: On-site
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Employment
Full-time — employment source
Employment type in the employer’s posting: Full-time
From the employer’s posting

What you’ll work on

Full posting
  • Deliver independently Data Science projects, bring an e2e product-oriented mindset

  • Lead pre-sales technical discussions, demonstrating the value and capabilities of our analytics solutions.

  • Collaborate with cross-functional teams to integrate AI/ML solutions into the company's product offerings.

From the employer’s posting
5 years of experience in different Data Science topics (e.g. machine learning, LLM, deep learning) Deliver independently Data Science projects, bring an e2e product-oriented mindset Engage directly with clients to understand their business objectives and translate them into technical requirements.
Engage directly with clients to understand their business objectives and translate them into technical requirements. Lead pre-sales technical discussions, demonstrating the value and capabilities of our analytics solutions. Collaborate with cross-functional teams to integrate AI/ML solutions into the company's product offerings.
Lead pre-sales technical discussions, demonstrating the value and capabilities of our analytics solutions. Collaborate with cross-functional teams to integrate AI/ML solutions into the company's product offerings. Provide thought leadership and mentorship within the team, fostering a culture of continuous learning and innovation.

What you’ll bring

All qualifications

Core experience

  • 5 years of experience in data science or a related field.
  • Strong Python and SQL skills
  • Familiarity with database systems (SQL, NoSQL)
  • Experience with deploying ML models in production environments
  • Hands-on experience with LLM projects, machine learning, deep learning.
  • Experience with LangChain / LlamaIndex
Qualification wording
5 years of experience in data science or a related field.
Strong Python and SQL skills
Familiarity with database systems (SQL, NoSQL)
Experience with deploying ML models in production environments
Hands-on experience with LLM projects, machine learning, deep learning.
Experience with LangChain / LlamaIndex
Apply at Hiflylabs

Posting record

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Likely evergreenReposted 3 times since Aug 7, 2026. A role that keeps coming back is often kept open to collect applications rather than to fill one seat.

Status in our records
Live
First seen by us
Oct 23, 202612 days ago
Recorded sightings
15
Last seen by us
Nov 4, 2026
Reposted
3 times since Aug 7, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications. We count a repost when the same title and location comes back as a new listing within 60 days of the last one coming down. Some hiring systems expire listings on a schedule, so repost rates vary by system.

How this job compares

Time since we first saw it

Day 12

Similar jobs usually come down between day 7 and day 55.

From 9,990 similar postings that came down. Coming down is not always a hire.

Hiflylabs is hiring

5 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Hiring is picking up
  • Takes jobs down at a usual pace
  • 100% of open jobs were reposted
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • SQL
  • AWS
  • Azure
  • Databricks
  • MLflow
  • NoSQL
  • SageMaker
  • FastAPI
  • Flask
  • Hugging Face
  • LightGBM
  • Streamlit
  • GCP
  • scikit-learn
Where the posting names them
Technical requirements: - Strong Python and SQL skills - Leverage cloud-based data science tools on AWS (SageMaker, Bedrock), Azure, or GCP for scalable model training and deployment
- Databricks / distributed computing / scalable ML - Familiarity with database systems (SQL, NoSQL) - ML Lifecycle management (e.g.: MLFlow / wandb)
- Strong Python and SQL skills - Leverage cloud-based data science tools on AWS (SageMaker, Bedrock), Azure, or GCP for scalable model training and deployment - IDE (e.g.: Jupyter, VSCode)
- Web frameworks (e.g.: Streamlit / FastAPI / Flask) - Automatization pipelines on cloud (e.g.: Azure Functions, AWS Lambda, Databricks notebook jobs) - API integration
Nice to have: - Databricks / distributed computing / scalable ML - Familiarity with database systems (SQL, NoSQL)
- Familiarity with database systems (SQL, NoSQL) - ML Lifecycle management (e.g.: MLFlow / wandb) - Web frameworks (e.g.: Streamlit / FastAPI / Flask)
- ML Lifecycle management (e.g.: MLFlow / wandb) - Web frameworks (e.g.: Streamlit / FastAPI / Flask) - Automatization pipelines on cloud (e.g.: Azure Functions, AWS Lambda, Databricks notebook jobs)
- NLP experience / affinity: Understand concepts of text classification, information extraction - Generative AI & LLM frameworks - HuggingFace / transformers, OpenAI; proprietary API & open-source models - Understand concepts of RAG, build & maintain pipeline, understand concepts of pretraining, fine-tuning
- Version control Git / BitBucket / AZ DevOps - Core machine learning libraries (sklearn, LightGBM, torch) - Traditional ML projects (supervised and unsupervised)

Your next step

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Has Hiflylabs posted this job before?

Yes. We’ve followed 3 other Senior Data Scientist with AI product mindset jobs there since June 2026. 3 came down, usually after about 13 days.

  1. BudapestCame down after 2 days, first seen Jun 2
  2. BudapestCame down after 13 days, first seen Sep 24
  3. BudapestCame down after 13 days, first seen Oct 8
  4. This jobUp 13 days so far, first seen Oct 23

If this one keeps the same pace, it may come down around November 5.

Large employers often post one title for several teams, so these can be separate openings.

About the role

We file this job under Data Scientist, by the work the posting describes.

Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.

Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.

Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.

US government figures for data scientists

Median yearly pay, May 2025
$120,230
Expected change, 2025 to 2035
34.6% more jobsagainst 3.5% for all jobs

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.

Job description

View original posting ↗

Job Description

Responsibilities

  • 5 years of experience in different Data Science topics (e.g. machine learning, LLM, deep learning)

  • Deliver independently Data Science projects, bring an e2e product-oriented mindset

  • Engage directly with clients to understand their business objectives and translate them into technical requirements.

  • Lead pre-sales technical discussions, demonstrating the value and capabilities of our analytics solutions.

  • Collaborate with cross-functional teams to integrate AI/ML solutions into the company's product offerings.

  • Provide thought leadership and mentorship within the team, fostering a culture of continuous learning and innovation.

  • Stay abreast of industry trends and advancements in AI/ML to ensure our solutions remain cutting-edge.

Qualifications

General qualifications:

  • Fluent English speaker with excellent communication skills, comfortable in client-facing roles.

  • 5 years of experience in data science or a related field.

  • Hands-on experience with LLM projects, machine learning, deep learning.

  • Affinity to building product / product-oriented vision

  • Domain expertise in any of the following fields is highly preferred: international finance, healthcare, pharma or meteorology.

Technical requirements:

  • Strong Python and SQL skills

  • Leverage cloud-based data science tools on AWS (SageMaker, Bedrock), Azure, or GCP for scalable model training and deployment

  • IDE (e.g.: Jupyter, VSCode)

  • Version control Git / BitBucket / AZ DevOps

  • Core machine learning libraries (sklearn, LightGBM, torch)

  • Traditional ML projects (supervised and unsupervised)

  • NLP experience / affinity: Understand concepts of text classification, information extraction

  • Generative AI & LLM frameworks - HuggingFace / transformers, OpenAI; proprietary API & open-source models

  • Understand concepts of RAG, build & maintain pipeline, understand concepts of pretraining, fine-tuning

Nice to have:

  • Databricks / distributed computing / scalable ML

  • Familiarity with database systems (SQL, NoSQL)

  • ML Lifecycle management (e.g.: MLFlow / wandb)

  • Web frameworks (e.g.: Streamlit / FastAPI / Flask)

  • Automatization pipelines on cloud (e.g.: Azure Functions, AWS Lambda, Databricks notebook jobs)

  • API integration

  • Experience with deploying ML models in production environments

  • Experience with LangChain / LlamaIndex

  • Understanding of LLM Agents, agentic behavior, prompt engineering

  • Being able to differentiate what 'needs' LLMs and what can be solved with traditional ML / NLP

Additional Information

Why us?

  • Diverse projects: In each assignment there is always something new either on the technical or on the business side that helps you grow.

  • Cutting edge technology: You will work with many of the most up-to-date technologies and tools.

  • Strong and motivating team: We stress the importance of working together in tight-knit, cohesive teams in which members help each other to reach the common goal.

  • Work-life balance: We help you to feel good individually as well, and coordinate work so as it should align with your leisure activities.

  • Professional development: There are team gatherings on a regular schedule where colleagues can share their knowledge, and have deep technical discussions.

  • Focus on company culture: In addition to our business and professional achievements we are proud of the social bonding in the company, which is based on mutual respect and helping one another.

  • Personal mentoring: You will have your own mentor (just like everybody at Hiflylabs) who you can turn to with professional issues as well as with personal ones.

Company Description

Hiflylabs is a Budapest-based company. We have 250+ employees at this moment and we are constantly thriving. Our application development team and business intelligence experts work to provide effective solutions to business problems.

Our professional team has proved its expertise through 10 years of experience, participating in multiple Business Intelligence projects - both Hungarian and international - in various industries, such as the financial, telecommunication and energy sectors.

We deliver a wide portfolio of innovative business solutions that include Data Warehouses, Business Intelligence, Data Analytics. In the last few years we have acquired a high level of competence in Application Development.

Hiflylabs is committed to innovation, and encourages the realization of innovative initiatives in the form of independent startups.

Get an insight on how we work and check out our Website, LinkedIn page and YouTube channel!

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Budapest, Hungary

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