Data Scientist

16k - 21k PLN/ mies.B2B
MidFull-time·B2B
#366448·Dodano wczoraj·0
Źródło: nofluffjobs.com
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Tech Stack / Keywords

PythonSQLClassical MLData visualizationData scienceMLNumPypandasscikit-learnMatplotlibDashboardingCloudsGenAILLMsData engineeringCommunication skillsCloud platformGCPAzureTableauBINLPAI

Firma i stanowisko

deepsense.ai is an AI company collaborating with partners like OpenAI, NVIDIA, and LangChain, working on projects involving LLMs, MLOps, Edge Solutions, Computer Vision, and Predictive Analytics across industries such as software, pharma, manufacturing, retail, telecoms, and media.


Wymagania

  • Minimum of 3 years of experience in Data Science.
  • Proficiency in classical ML techniques (linear regression, feature selection, predictive modeling, time series).
  • Experience with non-linear ML methods (gradient boosting, random forest, XGBoost, LightGBM, CatBoost).
  • Fluent programming skills in Python and libraries such as NumPy, pandas, scikit-learn.
  • Effective data management and analysis using SQL.
  • Ability to create visualizations with matplotlib, seaborn, plotly.
  • Strong communication skills to explain complex concepts simply.
  • Bonus: experience in data engineering, cloud platforms (AWS, GCP, Azure), dashboarding tools (Tableau, Power BI, Dash), NLP, and Generative AI/LLMs.

Obowiązki

  • Deliver end-to-end data-driven solutions using classical and non-linear ML techniques.
  • Program in Python using libraries such as NumPy, pandas, and scikit-learn.
  • Manage and analyze data using SQL.
  • Create clear and engaging visualizations using matplotlib, seaborn, and plotly.
  • Translate data into actionable business insights and recommendations.
  • Collaborate with partners and contribute to open-source projects.
  • Work on diverse projects including exploratory data analysis, feature engineering, predictive modeling, time-series analysis, data visualization, and dashboard development.

Oferta

  • Sport subscription
  • Training budget
  • Private healthcare
  • Lunch card
  • Small teams
  • International projects
  • Free coffee
  • Canteen
  • Free snacks
  • Free beverages
  • Free lunch
  • In-house trainings
  • Modern office
  • No dress code
  • Free breakfast
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