.Hey there, future Data Scientist at Enlitia! Ready to power up our innovative projects in the renewable energy sector? As a key player in our team, you'll be at the forefront of developing predictive algorithms, monitoring performance, optimizing processes, and conducting insightful data analysis. Your role will involve collaborating closely with cross-functional teams to understand project requirements and effectively communicating results to both technical and non-technical stakeholders. If you're a highly organized and motivated professional with a passion for sustainability, we're eager to hear from you!Key ResponsibilitiesData Analysis and Modelling:Dive deep into large and complex datasets to uncover patterns, trends, and golden nuggets of insight.Craft and deploy statistical models and machine learning algorithms that crack business problems wide open.Conduct hypothesis testing and A/B experiments to validate your findings like a master.Data Management:Extract, clean, and preprocess data from a variety of sources, ensuring top-notch data quality and consistency.Build and maintain datasets and data pipelines that are as smooth as a well-oiled machine.Team up with data engineers to optimize data storage and retrieval processes for peak efficiency.Business Collaboration:Partner with stakeholders to grasp business objectives and data requirements with laser-like precision.Turn complex analytical findings into actionable business recommendations that hit the mark.Present insights and results to non-technical audiences with visualizations and reports that make the data dance.Tool And Technology Utilization:Harness the power of statistical and machine learning tools (e.G., R, Python, SAS) to analyze data.Use data visualization tools (e.G., Grafana, Matplotlib, notebooks) to communicate your findings.Tap into big data technologies (e.G., Hadoop, Spark) for large-scale data processing.Continuous Learning:Stay on the cutting edge of data science, machine learning, and related fields to keep your skills razor-sharp.Experiment with new tools, techniques, and methodologies to keep pushing the envelope of data science capabilities.Minimum Requirements:Hold a BSc, MSc, or PhD in Computer Science, Electronic Engineering, Biomedical Engineering, Statistics, Mathematics, or Physics.3+ years of experience in data science or a related field.Proven experience with statistical analysis and machine learning, ideally with tabular and time-series data.Proficiency in programming languages, mainly Python and SQL.Familiarity with data visualization and dashboarding tools (e.G., Grafana, PowerBI).Knowledge of concepts and techniques in NLP (Natural Language Processing) is a plus.Understanding of big data frameworks and tools (e.G., Hadoop, Spark) is a plus.Excellent problem-solving and analytical skills.Strong communication and presentation abilities.Ability to work collaboratively in a team environment.Attention to detail and a commitment to data quality
