Data Scientist
Role details
Job location
Tech stack
Job description
Speedcast delivers highly customizable, mission-critical communication solutions for remote sites worldwide. As a Data Scientist, you will work closely with business stakeholders to understand challenges and objectives, transforming complex data into meaningful insights that support business decisions., * Develop and implement data models, analytics solutions, and reporting capabilities to support business objectives.
- Analyse large and complex datasets to identify trends, patterns, and opportunities for improvement.
- Build, test, and maintain statistical and machine learning models.
- Support data integration and ETL processes, ensuring data quality and consistency across systems.
- Collaborate with stakeholders to gather requirements and translate business needs into analytical solutions.
- Create dashboards, reports, and visualisations that provide actionable insights.
- Assist in the deployment, monitoring, and continuous improvement of data science solutions.
- Identify opportunities to improve processes, data quality, and operational efficiency.
- Work closely with engineering, product, and business teams to deliver high-quality solutions.
Requirements
The successful candidate will be passionate about data, analytics, and problem-solving, with the ability to work independently while collaborating effectively with cross-functional teams. You will contribute to the development of data-driven solutions and support the delivery of analytics and machine learning initiatives across the organisation., * 3-5 years of experience in Data Science, Analytics, Machine Learning, or a related field.
- Experience developing and implementing data models, analytical solutions, and machine learning algorithms.
- Strong programming skills in Python and experience with data analysis tools and libraries.
- Experience working with SQL and relational databases such as MySQL and PostgreSQL.
- Understanding of ETL processes, data modelling, and data warehousing concepts.
- Knowledge of machine learning techniques and statistical analysis methods.
- Experience working with cloud-based data platforms and services.
- Familiarity with big data technologies such as Apache Spark, Hadoop, Amazon EMR, or Kinesis is advantageous.
- Experience using version control tools such as Git or Bitbucket.
- Strong analytical and problem-solving skills with attention to detail.
- Excellent communication skills and the ability to explain technical concepts to both technical and non-technical audiences.
- Ability to work effectively in a collaborative and fast-paced environment.
Even better if you have:
- Experience with Natural Language Processing (NLP) or image processing techniques.
- Exposure to AWS services and cloud-native data solutions.
- AWS certifications (e.g., AWS Certified Developer or AWS Solutions Architect).
- Experience working in Agile/Scrum environments.
- Knowledge of CI/CD pipelines and deployment practices.
- Experience with data governance and data quality frameworks.