Data Scientist

Responsibilities:

• Develop Advanced Machine Learning Models: Leverage Python and machine learning libraries to design and implement predictive models, collaborating closely with data engineers to integrate models into existing pipelines.
  
• Optimize Data Pipelines for ML: Enhance existing data pipelines to accommodate machine learning model inputs and outputs, ensuring seamless integration and efficient data flow.
  
• Collaborate on Data Processing Infrastructure: Work closely with the data engineering team to enhance infrastructure capabilities for model training, validation, and deployment, using tools like Apache Kafka and Databricks.
  
• Conduct Exploratory Data Analysis (EDA): Explore large datasets, perform statistical analysis, and identify patterns or trends crucial for model development and business insights.
  
• Validate and Deploy ML Models: Validate model performance, fine-tune algorithms, and deploy models into production environments, ensuring scalability and reliability.
  
• Contribute to Data-Driven Decision Making: Collaborate with stakeholders to translate model outputs into actionable insights, facilitating informed business decisions.
  
• Stay Current with ML Trends: Continuously research and implement the latest advancements in machine learning techniques and technologies to enhance predictive models and strategies.

Requirements:

• Education: Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or related fields.
  
• Technical Skills: Proficiency in SQL and Python is a must. Solid understanding and practical experience in machine learning libraries (such as TensorFlow, scikit-learn, or PyTorch) and data manipulation tools (e.g., Pandas, NumPy).
  
• Data Engineering Foundation: Experience in designing and implementing data pipelines, familiarity with Apache Kafka, Databricks, and Delta Tables.
  
• Advanced Modeling Skills: Proven track record of developing and deploying machine learning models, understanding model evaluation metrics, and optimization techniques.
  
• Collaboration: Excellent communication skills to collaborate effectively across multidisciplinary teams, translating technical findings into actionable insights for non-technical stakeholders.
  
• Analytical Thinking: Strong analytical and problem-solving skills, with the ability to dissect complex problems and derive practical solutions.
  
• Adaptability: Ability to work in a fast-paced, evolving environment, managing multiple priorities and delivering quality results within deadlines.
  

Our team is composed of experts in their fields who are passionate about delivering high-quality work and maintaining a positive work culture. We value innovation, teamwork, and personal growth. As an experienced Data Scientist, you will have the opportunity to make a significant impact on our projects and contribute to the success of our organization. If you are ready to embrace exciting challenges and foster a culture of excellence, we encourage you to apply.

What do we offer:

• Work remotely from anywhere in the world, with a fully remote team, and enjoy a mutually agreed schedule that fits your needs. (Core US working hours) 
• Work primarily with US-based colleagues, providing you with the opportunity to collaborate with people from diverse backgrounds and skill sets.
• Use your skills and expertise to make a significant impact on the delivery of projects in our company
• Work in a supportive environment that values your contribution and provides you with the resources and training you need to grow in your career.
• Enjoy a 40-hour workweek that provides you with a healthy work-life balance, and the time to pursue your personal and professional goals outside of work.