1 to 25 of 77 Remote Jupyter Jobs

Experience from a university project, hackathon, or internship involving AI or machine learning Understanding of neural networks, NLP, or computer vision concepts Experience using Jupyter notebooks, Git, or cloud platforms (AWS, GCP, Azure) Knowledge of SQL or data wrangling techniques What You’ll Gain Real-World Experience : Work on live ...

using Large Language Models Build processes for extracting, cleaning and transforming data (SQL/Python) Ad-hoc data mining for insights using Python + Jupyter notebooks Present insights and predictions in live dashboards using Tableau/PowerBI Lead the presentation of findings to clients through written documentation, calls and presentations ...

understanding of ML workflows: data cleaning, model development, tuning, evaluation Familiarity with model deployment, API development, or real world ML product integration Experience with Jupyter, Colab, or cloud based ML platforms Strong analytical, problem solving, and communication skills Comfortable working remotely and collaborating across time zones Nice to Have Experience ...

recommendations to non-technical stakeholders. Ideal Qualifications: Strong applied data science or analytics experience in business settings. Proficiency in Python or R (pandas, NumPy, Jupyter) and strong SQL skills. Experience with data visualization tools (e.g., Tableau, Power BI). Solid understanding of statistical modeling, experimentation, and A/B testing. ...

recommendations to non-technical stakeholders. Ideal Qualifications: Strong applied data science or analytics experience in business settings. Proficiency in Python or R (pandas, NumPy, Jupyter) and strong SQL skills. Experience with data visualization tools (e.g., Tableau, Power BI). Solid understanding of statistical modeling, experimentation, and A/B testing. ...

recommendations to non-technical stakeholders. Ideal Qualifications: Strong applied data science or analytics experience in business settings. Proficiency in Python or R (pandas, NumPy, Jupyter) and strong SQL skills. Experience with data visualization tools (e.g., Tableau, Power BI). Solid understanding of statistical modeling, experimentation, and A/B testing. ...

recommendations to non-technical stakeholders. Ideal Qualifications: Strong applied data science or analytics experience in business settings. Proficiency in Python or R (pandas, NumPy, Jupyter) and strong SQL skills. Experience with data visualization tools (e.g., Tableau, Power BI). Solid understanding of statistical modeling, experimentation, and A/B testing. ...

recommendations to non-technical stakeholders. Ideal Qualifications: Strong applied data science or analytics experience in business settings. Proficiency in Python or R (pandas, NumPy, Jupyter) and strong SQL skills. Experience with data visualization tools (e.g., Tableau, Power BI). Solid understanding of statistical modeling, experimentation, and A/B testing. ...

recommendations to non-technical stakeholders. Ideal Qualifications: Strong applied data science or analytics experience in business settings. Proficiency in Python or R (pandas, NumPy, Jupyter) and strong SQL skills. Experience with data visualization tools (e.g., Tableau, Power BI). Solid understanding of statistical modeling, experimentation, and A/B testing. ...

recommendations to non-technical stakeholders. Ideal Qualifications: Strong applied data science or analytics experience in business settings. Proficiency in Python or R (pandas, NumPy, Jupyter) and strong SQL skills. Experience with data visualization tools (e.g., Tableau, Power BI). Solid understanding of statistical modeling, experimentation, and A/B testing. ...

recommendations to non-technical stakeholders. Ideal Qualifications: Strong applied data science or analytics experience in business settings. Proficiency in Python or R (pandas, NumPy, Jupyter) and strong SQL skills. Experience with data visualization tools (e.g., Tableau, Power BI). Solid understanding of statistical modeling, experimentation, and A/B testing. ...

recommendations to non-technical stakeholders. Ideal Qualifications: Strong applied data science or analytics experience in business settings. Proficiency in Python or R (pandas, NumPy, Jupyter) and strong SQL skills. Experience with data visualization tools (e.g., Tableau, Power BI). Solid understanding of statistical modeling, experimentation, and A/B testing. ...

recommendations to non-technical stakeholders. Ideal Qualifications: Strong applied data science or analytics experience in business settings. Proficiency in Python or R (pandas, NumPy, Jupyter) and strong SQL skills. Experience with data visualization tools (e.g., Tableau, Power BI). Solid understanding of statistical modeling, experimentation, and A/B testing. ...

recommendations to non-technical stakeholders. Ideal Qualifications: Strong applied data science or analytics experience in business settings. Proficiency in Python or R (pandas, NumPy, Jupyter) and strong SQL skills. Experience with data visualization tools (e.g., Tableau, Power BI). Solid understanding of statistical modeling, experimentation, and A/B testing. ...

recommendations to non-technical stakeholders. Ideal Qualifications: Strong applied data science or analytics experience in business settings. Proficiency in Python or R (pandas, NumPy, Jupyter) and strong SQL skills. Experience with data visualization tools (e.g., Tableau, Power BI). Solid understanding of statistical modeling, experimentation, and A/B testing. ...

recommendations to non-technical stakeholders. Ideal Qualifications: Strong applied data science or analytics experience in business settings. Proficiency in Python or R (pandas, NumPy, Jupyter) and strong SQL skills. Experience with data visualization tools (e.g., Tableau, Power BI). Solid understanding of statistical modeling, experimentation, and A/B testing. ...

recommendations to non-technical stakeholders. Ideal Qualifications: Strong applied data science or analytics experience in business settings. Proficiency in Python or R (pandas, NumPy, Jupyter) and strong SQL skills. Experience with data visualization tools (e.g., Tableau, Power BI). Solid understanding of statistical modeling, experimentation, and A/B testing. ...

recommendations to non-technical stakeholders. Ideal Qualifications: Strong applied data science or analytics experience in business settings. Proficiency in Python or R (pandas, NumPy, Jupyter) and strong SQL skills. Experience with data visualization tools (e.g., Tableau, Power BI). Solid understanding of statistical modeling, experimentation, and A/B testing. ...

recommendations to non-technical stakeholders. Ideal Qualifications: Strong applied data science or analytics experience in business settings. Proficiency in Python or R (pandas, NumPy, Jupyter) and strong SQL skills. Experience with data visualization tools (e.g., Tableau, Power BI). Solid understanding of statistical modeling, experimentation, and A/B testing. ...

recommendations to non-technical stakeholders. Ideal Qualifications: Strong applied data science or analytics experience in business settings. Proficiency in Python or R (pandas, NumPy, Jupyter) and strong SQL skills. Experience with data visualization tools (e.g., Tableau, Power BI). Solid understanding of statistical modeling, experimentation, and A/B testing. ...

recommendations to non-technical stakeholders. Ideal Qualifications: Strong applied data science or analytics experience in business settings. Proficiency in Python or R (pandas, NumPy, Jupyter) and strong SQL skills. Experience with data visualization tools (e.g., Tableau, Power BI). Solid understanding of statistical modeling, experimentation, and A/B testing. ...

recommendations to non-technical stakeholders. Ideal Qualifications: Strong applied data science or analytics experience in business settings. Proficiency in Python or R (pandas, NumPy, Jupyter) and strong SQL skills. Experience with data visualization tools (e.g., Tableau, Power BI). Solid understanding of statistical modeling, experimentation, and A/B testing. ...

recommendations to non-technical stakeholders. Ideal Qualifications: Strong applied data science or analytics experience in business settings. Proficiency in Python or R (pandas, NumPy, Jupyter) and strong SQL skills. Experience with data visualization tools (e.g., Tableau, Power BI). Solid understanding of statistical modeling, experimentation, and A/B testing. ...

recommendations to non-technical stakeholders. Ideal Qualifications: Strong applied data science or analytics experience in business settings. Proficiency in Python or R (pandas, NumPy, Jupyter) and strong SQL skills. Experience with data visualization tools (e.g., Tableau, Power BI). Solid understanding of statistical modeling, experimentation, and A/B testing. ...

recommendations to non-technical stakeholders. Ideal Qualifications: Strong applied data science or analytics experience in business settings. Proficiency in Python or R (pandas, NumPy, Jupyter) and strong SQL skills. Experience with data visualization tools (e.g., Tableau, Power BI). Solid understanding of statistical modeling, experimentation, and A/B testing. ...