Data Scientist

SUMMARY:
We are seeking a highly skilled and experienced Data Scientist to join our team and contribute to the development and implementation of a PowerBI solution on the Azure platform. As a Data Scientist, you will be responsible for utilizing advanced analytics, machine learning, and statistical modelling techniques to extract insights from data, build predictive models, and drive data-driven decision-making. Your expertise in data analysis, modelling, and visualization will play a crucial role in enhancing our PowerBI solution and delivering valuable insights to our stakeholders.

POSITION INFO:
Job Details:

• Collaborate closely with business stakeholders to understand their requirements, identify key challenges, and define project goals and success criteria.
• Design and develop complex machine learning models and algorithms using techniques such as regression, classification, clustering, and time series analysis.
• Utilize programming languages such as Python and R, along with machine learning libraries and frameworks, to build and deploy scalable and efficient data science models.
• Leverage Azure services, including Azure Machine Learning, Azure Databricks, Azure Data Factory, and Azure Data Lake Storage, to facilitate data ingestion, pre-processing, analysis, and
• Perform exploratory data analysis, feature engineering, and data pre-processing tasks to ensure data quality and optimize model performance.
• Create visually compelling and interactive dashboards and reports using PowerBI, enabling stakeholders to gain insights and make data-driven decisions.
• Collaborate with cross-functional teams, including data engineers and developers, to integrate data science models into the PowerBI solution and ensure seamless data flow and
• Conduct thorough evaluations and assessments of model performance, iterate on models to improve accuracy and efficiency, and implement appropriate validation and testing
• Stay updated with the latest advancements in data science, machine learning, and Azure technologies, and proactively explore innovative solutions to enhance the PowerBI
• Provide guidance, mentorship, and knowledge sharing to junior data scientists, fostering their professional growth and contributing to the overall team's success.
• Maintain comprehensive documentation of the project, including model design, implementation details, data pipelines, and deployment processes.

• Bachelor’s degree or higher in Data Science, Statistics, Computer Science, or a related

• Minimum of 6 years of professional experience as a Data Scientist, with a focus on developing and implementing data science solutions using Azure and PowerBI.
• Strong expertise in statistical modelling, machine learning algorithms, and data visualization
• Proficiency in programming languages such as Python and R, with experience in using relevant libraries and frameworks for machine learning.
• Strong experience with Azure services, including Azure Machine Learning, Azure Databricks, Azure Data Factory, and Azure Data Lake Storage.
• In-depth knowledge of data pre-processing, feature engineering, and exploratory data
• Strong experience in creating interactive and visually appealing dashboards and reports using
• Familiarity with SQL and the ability to query and manipulate data for analysis and modelling
• Hands-on experience with Databricks for scalable data processing, analysis, and model
• Solid understanding of cloud computing concepts and experience working with Azure or other cloud platforms.
• Excellent problem-solving and analytical skills, with a focus on delivering practical and impactful solutions to business challenges.
• Strong communication and presentation skills, with the ability to effectively convey complex concepts and insights to technical and non-technical stakeholders.
• Proven track record of successfully delivering data science projects within tight deadlines and managing project resources effectively.

• Power BI
• Azure Data Lake
• Azure Databricks
• Azure SQL Database
• Azure Machine Learning
• Azure Data Factory
• Python or R programming languages
• Data pre-processing and cleaning tools (e.g., Pandas, NumPy)
• Statistical analysis and modelling tools (e.g., scikit-learn, TensorFlow, PyTorch)
• Version control systems (e.g., Git)
• SQL for data querying and manipulation
• Data visualization tools (e.g., matplotlib, seaborn)

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