In a world where vast amounts of data are being created in a multitude of different ways, Lumilinks exist to help companies collate and use data in an automated and compliant way, creating live and actionable insights. We help businesses across the entire data journey, eliminating silos and creating data transparency. This allows our clients to be data confident in making strategic and tactical decisions that will further their business and create automation that improves processes, compliance, capability and reduces costs. As a Data Scientist at Lumilinks, you will be at the forefront of our mission to leverage data-driven insights to solve complex problems and deliver innovative solutions. In this pivotal role, you will work collaboratively with a diverse team of data engineers, product managers, and data analysts to translate raw data into actionable strategies that drive growth and enhance our product offerings. You will be responsible for a wide range of activities, from collecting and pre-processing data to developing predictive models and generating insightful visualisations. Your analytical skills will be essential in identifying trends, patterns, and anomalies within data, enabling us to make informed decisions that align with our business objectives. In a fast-paced start-up environment, you will have the opportunity to take ownership of projects from inception to execution, experimenting with new methodologies and technologies. Your contributions will directly impact the direction of our products and services, offering you a unique chance to shape the future of our company. This is an exciting opportunity to contribute to the expansion of our data science company and make a significant impact in the field. - Analysing large datasets to extract meaningful insights and translating complex data findings into actionable recommendations for stakeholders. - Designing, developing, and validating machine learning models and statistical algorithms to address specific business challenges and improve decision-making processes. - Ensuring data quality by cleaning and pre-processing raw data, handling missing values, and transforming data into a suitable format for analysis. - : Identifying and creating new features from existing data that enhance the performance of predictive models. - Working closely with cross-functional teams, including product managers, engineers, and marketing, to understand business needs and align data science efforts with company goals. - : Creating compelling visualisations and dashboards using tools like Tableau, Power BI, or Python libraries (e.g., Matplotlib, Seaborn) to effectively communicate insights to both technical and non-technical audiences. - : Designing and conducting experiments to test hypotheses and measure the impact of changes in products or services, providing data-driven recommendations based on results. - : Collaborating with engineering teams to deploy data models into production, ensuring they are scalable and maintainable, and monitoring their performance over time. - : Continuously researching and learning about new technologies, methodologies, and industry trends to apply best practices in data science and enhance the company’s capabilities. - Maintaining thorough documentation of processes, methodologies, and findings to ensure transparency, reproducibility, and knowledge transfer within the team. - Providing guidance to junior team members or colleagues interested in data science, building a collaborative learning environment. - Participating in the development of the company’s data strategy, identifying opportunities for leveraging data to drive growth and innovation. - Eager to expand technical skills in areas such as machine learning, deep learning, natural language processing, or big data technologies to enhance expertise and effectiveness. - Aspiring to take on more responsibility in leading data science projects, from conception to implementation, and driving impactful outcomes for the business. - : Seeking opportunities to collaborate with various teams (such as engineering, product management, and marketing) to better understand their data needs and contribute to a data-driven culture. - : Aiming to eventually mentor junior data scientists, helping to nurture talent and contribute to the development of the data science community within the Lumilinks. - : Aspiring to establish a reputation as a knowledgeable contributor in the data science field. - : Interested in working on ground-breaking projects that leverage data science to solve complex problems, drive innovation, and contribute to the company's competitive advantage. - : Aspiring to progress to a more senior role, such as a lead data scientist or data science manager, to take on greater leadership responsibilities and influence the direction of data initiatives. - : Eager to contribute to projects that have a significant positive impact on business outcomes, such as improving customer experience, increasing efficiency, or driving revenue growth. - : Seeking to help build a culture of data-driven decision-making within Lumilinks, advocating for the use of data insights across all levels of the business. - : Aspiring to work with cutting-edge tools and technologies in data science, continuously exploring new methodologies that can enhance analytical capabilities and business outcomes. - A strong desire to explore data and uncover insights, constantly asking questions and seeking to understand the underlying patterns in the data. - : Ability to approach problems logically, breaking down complex issues into smaller, manageable components for effective analysis. - Willingness to embrace change and pivot quickly in response to new information, challenges, or shifting business priorities, which is often necessary in a start-up environment. - A team player who values input from colleagues, enjoys working with others across various departments, and contributes to a positive team dynamic. - A meticulous approach to data cleaning, analysis, and model development, ensuring accuracy and reliability in results. - : Strong ability to identify challenges and develop innovative solutions, leveraging data science techniques to address business problems. - : Proficient in conveying technical concepts and insights to non-technical stakeholders, ensuring clarity and understanding across Lumilinks. - Ability to handle setbacks and challenges with a positive attitude, maintaining motivation and focus on achieving goals. - A commitment to continuous professional development, staying updated with the latest trends, technologies, and methodologies in data science. - A strong understanding of ethical considerations in data handling and analysis, ensuring responsible use of data and adherence to privacy standards. - : Python: Proficient in Python for data analysis, machine learning, and automation. Familiarity with libraries such as Pandas, NumPy, Scikit-learn, and TensorFlow or PyTorch. R: Experience with R for statistical analysis and data visualisation. - : Advanced skills in data pre-processing, cleaning, and manipulation using tools like SQL and Pandas. Proficient in data exploration techniques to identify trends, patterns, and anomalies. - Strong understanding of statistical concepts, including probability, distributions, hypothesis testing, and regression analysis. - Experience with a range of machine learning algorithms (e.g., linear regression, decision trees, support vector machines, clustering) and understanding of model evaluation techniques (e.g., cross-validation, ROC-AUC). Familiarity with advanced techniques such as deep learning, natural language processing, or reinforcement learning. - Proficient in data visualisation tools and libraries (e.g., Matplotlib, Seaborn, Tableau, or Power BI) to effectively communicate insights and findings. - Familiarity with big data processing frameworks such as Apache Spark, Hadoop, or distributed computing concepts. - Experience with cloud platforms (e.g., AWS, Google Cloud, Azure) for data storage and model deployment, including knowledge of services like AWS S3, Lambda, or Google BigQuery. - Strong understanding of version control systems, particularly Git, for collaborative development and code management. - Experience in designing, building, and maintaining data pipelines for ETL (Extract, Transform, Load) processes. - Understanding of the industry and market dynamics relevant to the start-up, allowing for informed data-driven decision-making.