Data Scientist Manager

** - Advanced Data Analysis and Modeling: You will be responsible for feature selection, dimensionality reduction, model evaluation, and validation. - Domain Knowledge: Utilize your expertise in the domain to ask relevant questions and create significant solutions. - Business Insight: Understand business operations, market dynamics, and financial implications to prioritize data science projects aligning with FDOs goals. - Out of Code Computing: Utilize libraries supporting out-of-core computing like Dask in Python for processing large datasets. - Machine Learning: Provide technical directions on models and techniques, and demonstrate advanced machine learning skills for complex models. - Partnership and Communication: Effectively communicate with non-technical customers, articulate findings through visualization, and collaborate with domain experts. - Continuous Learning: Stay updated on technical data science with domain understanding. - Data Ethics and Privacy: Implement anonymization, pseudonymization, and adhere to data retention policies. - Database Management: Utilize SQL or NoSQL databases for querying and extracting data. - Project Management: Lead data science projects effectively, including prioritizing, planning, and delivering results within set timelines. - Statistical Analysis and Mathematics: Apply solid statistical methods and mathematical concepts for data analysis and modeling. **Qualification Required:** - Experience: A minimum of 10 years of experience in a leadership role in data analysis with a master's degree in a relevant field. - Skills: Proficiency in Python, SQL, Azure data bricks, statistics, and mathematics. - Soft Skills: Active listening, problem translation, communication, and partnership. - Data Sources: Familiarity with SAP, Concur, Salesforce, Workday, and Excel files. - Tools and Libraries: Working knowledge of Pandas, PySpark, NumPy, SciPy, NLP, and fuzzy matching logic. - Certifications: Certified in SQL, Machine learning, Azure data bricks. In addition to the above role-specific requirements, you may be expected to travel up to 10% for this position. This role is eligible for relocation within the country and offers a hybrid of office/remote working options. Legal Disclaimer: The company is an equal opportunity employer and values diversity. They do not discriminate on any basis and provide adjustments/accommodations for individuals with accessibility needs during the recruitment process. If you are passionate about data science, have leadership qualities, and are looking to make a significant impact in the energy sector, this role as a Data Scientist Manager could be the next step in advancing your career. As a Data Scientist Manager in the Finance Team at a global energy business, your role will involve leading and contributing to sophisticated data analysis, modeling, and machine learning projects. You will play a crucial role in extracting actionable insights, driving strategic decision-making, and enhancing business processes through data-driven solutions. **

** - Advanced Data Analysis and Modeling: You will be responsible for feature selection, dimensionality reduction, model evaluation, and validation. - Domain Knowledge: Utilize your expertise in the domain to ask relevant questions and create significant solutions. - Business Insight: Understand business operations, market dynamics, and financial implications to prioritize data science projects aligning with FDOs goals. - Out of Code Computing: Utilize libraries supporting out-of-core computing like Dask in Python for processing large datasets. - Machine Learning: Provide technical directions on models and techniques, and demonstrate advanced machine learning skills for complex models. - Partnership and Communication: Effectively communicate with non-technical customers, articulate findings through visualization, and collaborate with domain experts. - Continuous Learning: Stay updated on technical data science with domain understanding. - Data Ethics and Privacy: Implement anonymization, pseudonymization, and adhere to data retention policies. - Database Management: Utilize SQL or NoSQL databases for querying and extracting data. - Project Management: Lead data science projects effectively, including prioritizing, planning, and delivering results within set timelines. - Statistical Analysis and Mathematics: Apply solid statistical methods and mathematical concepts for data analysis and modeling. **Qualification Required:** - Experience: A minimum of 10 years of experience in a leadership role in data analy