Must have

• Python

• SQL

• Classical ML

• Data visualization

• Polish

• English

Nice to have

• Dashboarding

• Clouds

• GenAI

• LLMs

Requirements description

You Must Have:

• minimum of 4-5 years of experience in data science, demonstrating a proven track record of delivering comprehensive data science solutions from start to finish,
• skilled in Python with strong familiarity with data science libraries like NumPy, pandas, and scikit-learn,
• proficient in SQL for effective data management and querying,
• experiance in classical ML: linear regression, time series, feature selection methods, predictive modeling
• strong skills in creating data visualizations, enabling clear and impactful presentation of analytical results, familiarity with visualisation Python tools (eg. matplotlib, seaborn, plotly, etc.),
• outstanding written and verbal communication skills,
• excellent problem-solving capabilities, with the ability to clearly articulate complex ideas and concepts.

Bonus Skills:

• experience with creating interactive dashboards (e.g., in Tableau, Power BI, or Plotly Dash)
• familiarity with cloud platforms for ML deployment (GCP, AWS, Azure)
• familiarity with Generative AI and Large Language Models (LLMs)

Offer description

deepsense.ai is seeking a talented Senior Data Scientist to join our team, focusing on creating and implementing data-driven insights and models. In this role, you’ll collaborate with our engineers to analyze and interpret complex data sets, addressing diverse challenges across various industries. Your work will encompass the entire spectrum of data science processes, from initial data exploration and model development to deployment and optimization, with an emphasis on innovative and impactful solutions.

Your responsibilities

1. develop and implement scalable models and analytics solutions to address real-world challenges,
2. translate business requirements into data-driven insights and actionable goals,
3. optimize data pipelines to enhance data processing and analysis capabilities,
4. design automated processes for data analysis and report generation,
5. ensure seamless integration of data solutions within client environments,
6. stay updated with the latest data science technologies and methodologies to apply them effectively,

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