Data Scientist

As a Data Scientist at Scalepex, you will play a pivotal role in analyzing complex datasets to derive actionable insights that drive business decisions. You will collaborate with cross-functional teams to develop and deploy machine learning models, ensuring data-driven strategies align with client objectives in a fully remote environment.

Key Responsibilities

• Data Analysis & Modeling: Apply advanced statistical analysis and machine learning techniques to extract insights from large, complex datasets.

• Model Development: Design, develop, and deploy predictive models, optimization systems, and other machine learning products.

• Data Visualization: Create compelling visualizations to communicate findings to both technical and non-technical stakeholders.

• Collaboration: Work closely with data engineers and data architects to integrate models into production systems.

• Project Leadership: Lead end-to-end data science projects, ensuring alignment with business objectives and stakeholder requirements.

Requirements

Qualifications

• Experience: Minimum of 3 years of hands-on experience as a Data Scientist or Data Analyst.

• Technical Skills:

  • Proficient in programming languages such as Python and/or R.

  • Experience with SQL and relational databases.

  • Familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn).

  • Experience with data visualization tools like Power BI or Tableau.

• Education: Bachelor’s degree in Data Science, Computer Science, Mathematics, Statistics, or a related field. A Master’s degree or advanced certification is preferred.

• Soft Skills:

  • Strong problem-solving and analytical skills.

  • Excellent communication skills in English.

  • Ability to work independently in a remote setting.

Preferred Qualifications

• Experience with cloud platforms such as AWS, Azure, or Google Cloud.

• Familiarity with big data processing tools like Spark or Hadoop.

• Knowledge of Natural Language Processing (NLP) techniques.

• Experience in deploying machine learning models using platforms like Databricks or MLflow.