Senior Data Scientist

Company Description

Unleash your ambition as a Senior Data Scientist! We are in search of a professional with substantial data science experience who is ready to take on a driving role, contributing to our Data Competency Center at Sigma Software. This position will involve Solution assessment, guided pre-sales activities, architecture design composition, and more.

PROJECT

We are a team of over 160 professionals. We are very diverse, but there are a few things that bind us as a true team: our genuine passion for our work, our friendliness, and an unshakable optimism, no matter what.

We employ the Agile methodology coupled with technical excellence and the Kanban approach to deliver top-notch work and keep our customers satisfied. Our goal is to provide our clients with the best expertise in different domains to boost their business value and establish ourselves as their preferred tech partner.

Job Description

• Work in close collaboration with the client (PO) and other Team Leads to clarify technical requirements and expectations
• Translate intricate business problems into actionable, data-driven questions or hypotheses. This will involve liaising with stakeholders to understand the root issues and defining the specific questions to be answered through data analysis
• Gather data from diverse sources, pinpoint and resolve data quality issues and convert the data into a format suitable for analysis and modeling. This will necessitate the use of data wrangling techniques, data cleaning tools, and data quality checks
• Employ statistical methods, data visualization techniques and machine learning algorithms to unearth hidden patterns, trends, and anomalies within the data. These insights will guide the creation of effective models and solutions
• Choose and apply suitable machine learning or statistical models to address specific business issues. This involves grasping the problem at hand, selecting the right algorithms, training the models on the prepared data, and assessing their performance
• Collaborate with engineers to incorporate trained models into production environments, ensuring they can be used to make real-time predictions or decisions. This involves model deployment, performance monitoring, and ongoing maintenance
• Communicate complicated, data-driven insights and recommendations to stakeholders in a clear, concise, and actionable manner. This involves using storytelling techniques, visualizations, and presentations to effectively communicate the findings and their business decision implications
• Consistently research and stay abreast with the latest developments in data science, including new algorithms, techniques, and tools, and explore emerging technologies and methodologies. This involves attending conferences, reading research papers, and experimenting with innovative approaches
• Propose and contribute to training and improvement plans concerning analytical data engineering skills, standards, and processes

Qualifications

• 3-5+ years of experience with Python or R
• Experience with AWS/Azure
• Expertise in machine learning algorithms, including linear regression, clustering, classification, and recommendation systems
• Demonstrated ability to create clear, concise, and compelling visualizations using tools like ggplot2, matplotlib, or plotly, Power BI, Tableau, and Qlik
• Conceptual understanding of data analysis fundamentals, including ETL, data warehousing, and unstructured data
• A thorough understanding of deep learning fundamentals, including activation functions, backpropagation, CNNs, Transformers, transfer learning, and generative models
• Expertise in evaluating and selecting the most appropriate deep learning model for a given task, including assessing model performance metrics, identifying potential biases, and comparing different model architectures

Additional Information

PERSONAL PROFILE

• Analytical and Problem-Solving Skills:
• Demonstrated problem-solving and analytical thinking skills, with a proven track record of applying these skills to real-world challenges in order to identify problems, gather relevant data, and develop innovative solutions
• A mindset geared towards continuous learning, ensuring you keep up-to-date with the latest advancements in deep learning and adapt skills accordingly
• Actively participate in the evaluation of new tools for analytical data engineering or data science