Senior Data Scientist - OPS00021 at DevPro

, , Colombia -

Full Time

Start Date

Immediate

Expiry Date

21 Jan, 26

Salary

0.0

Posted On

23 Oct, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Science, Machine Learning, Python, PostgreSQL, Cloud Platforms, Communication Skills, Model Evaluation, Semantic Search, Data Engineering, Dataset Evaluation, Collaboration, BigQuery, Dataflow, Pandas, NumPy, scikit-learn, PyTorch

Industry

IT System Custom Software Development

Description

We are a US-based outsource software development company that has been delivering exceptional software experience to our clients since 2011, helping technology companies to become industry leaders. Over the past few years, we’ve been hiring specialists all over the world while our main development centers were in Ukraine. Now, we keep expanding and start growing our centers in different parts of the world. Dev.Pro is open to hire specialists from other countries as well as Ukrainians who live outside of Ukraine now. We stand with Ukraine and keep supporting our people by offering a friendly remote environment while adhering to the values of democracy, human rights, and state sovereignty. As a company of professionals, Dev.Pro offers challenging and interesting projects with world-leading clients, a modern technology stack, and career opportunities for both technical and non-technical specialists. About this opportunity We invite a Senior Data Scientist with a strong academic foundation and extensive practical experience applying ML models to real-world problems to join our team. In this role, you’ll closely collaborate with our Head of AI, data engineers, product teams, and international AI experts to design, evaluate, improve, and deploy ML solutions, supporting the growth and maturity of the Data Science function. What's in it for you: • Lead high-impact ML projects and see your work make a real impact in production • Collaborate with top AI and ML experts across Latin America, gaining hands-on experience building and refining advanced models • Enjoy a flexible hybrid setup that balances in-office collaboration with the freedom to work remotely Is that you? • Master’s degree or higher in Data Science, CS, Applied Math, or related field • 5-10 years of hands-on data science experience in fast-paced or startup environments • Strong ML and semantic search skills with hands-on model evaluation experience (precision, recall, F1, confusion matrices) • Strong proficiency in Python • Solid knowledge of PostgreSQL, including query optimization, schema design, and data transformations • Familiarity with cloud platforms, preferably GCP • Strong communication skills and ability to collaborate across teams • Upper-Intermediate English level Desirable: • Experience with Pandas, NumPy, scikit-learn, and PyTorch/TensorFlow • Experience with Supabase and Next.js or similar • Exposure to BigQuery and Dataflow pipelines • Experience with data labeling and information retrieval • Experience in distributed, multicultural team environments Key responsibilities and your contribution In this role, you’ll apply your expertise to build, evaluate, and scale robust ML solutions in close collaboration with international cross-functional teams. • Lead development and evaluation of ML models (semantic search, Cayenne/KNN-type algorithms, supervised labeling) • Design and improve processes for dataset evaluation and labeling accuracy • Collaborate with data engineers to ensure seamless model and data architecture integration • Work closely with ops and front-end engineers to deploy and integrate ML models into live applications • Run experiments, evaluate performance metrics, and iterate quickly • Collaborate with product, engineering, and leadership teams to translate business needs into scalable ML solutions

Responsibilities

In this role, you’ll apply your expertise to build, evaluate, and scale robust ML solutions in close collaboration with international cross-functional teams. You will lead the development and evaluation of ML models and collaborate with data engineers to ensure seamless integration.