AI Staffing Ninja
Location
Vadodara | India
Job description
As a Data Scientist, you will be responsible for analyzing complex datasets, developing models and algorithms, and providing insights that drive informed business decisions. You will collaborate with cross-functional teams to identify and solve data-related problems, and communicate your findings effectively to both technical and non-technical stakeholders. Your work will contribute to improving processes, optimizing performance, and discovering new opportunities for the organization.
Responsibilities: Data Analysis: Identify, clean, and preprocess large datasets from various sources to extract meaningful insights and patterns. Apply statistical techniques and data mining algorithms to uncover trends, correlations, and anomalies. Model Development: Design, develop, and implement predictive models, machine learning algorithms, and statistical models to solve business problems and improve decision-making processes. This includes feature selection, model training, validation, and optimization. Data Visualization: Create visualizations and dashboards to present complex data in a clear and intuitive manner. Communicate findings and insights to stakeholders, including executives, managers, and other team members, through reports and presentations. Collaborative Problem Solving: Work closely with cross-functional teams, such as business analysts, engineers, and product managers, to understand their data needs and provide analytical solutions. Collaborate on projects and initiatives that require data-driven decision making. Experimentation and Testing: Design and execute experiments to evaluate the performance and effectiveness of models and algorithms. Conduct A/B testing and other statistical methods to validate hypotheses and optimize algorithms. Continuous Learning: Stay updated with the latest advancements in data science, machine learning, and related fields. Apply new methodologies and technologies to improve data analysis processes and enhance the quality of insights generated. Requirements: Education: Bachelor's or Master's degree in a quantitative field such as Computer Science, Statistics, Mathematics, or a related discipline. A Ph.D. in a relevant field can be advantageous but is not always required. Strong Analytical Skills: Proficiency in data analysis, statistical modeling, and machine learning techniques. Experience with programming languages such as Python or R, and familiarity with libraries and frameworks for data manipulation and analysis (e.g., NumPy, Pandas, scikit-learn). Problem-solving Abilities: Ability to approach complex problems with a structured and analytical mindset. Strong critical thinking and problem-solving skills to develop innovative solutions and models. Communication Skills: Excellent verbal and written communication skills to effectively convey complex technical concepts to both technical and non-technical stakeholders. The ability to present insights and findings in a clear and concise manner is essential. Business Acumen: Understanding of business operations, processes, and objectives. The ability to translate business requirements into data-driven solutions and provide actionable recommendations. Teamwork and Collaboration: Strong interpersonal skills and the ability to work effectively in cross-functional teams. The capacity to collaborate, listen, and communicate with team members from diverse backgrounds and areas of expertise. Data Manipulation and Visualization: Experience in working with large datasets, data cleaning, and data preprocessing techniques. Proficiency in data visualization tools such as Tableau, Power BI, or Matplotlib to create compelling visualizations and reports. Curiosity and Continuous Learning: A passion for data science and a desire to stay updated with emerging trends and technologies. Proactive attitude towards learning new methodologies and tools.Job tags
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