Senior Data Scientist
1 week ago
Roles & Responsibilities:
Gain a deep understanding of diverse data resources, including when and how to leverage them effectively while discerning which to avoid based on the context.
Analyze and manipulate complex, high-volume, multidimensional datasets from various sources using a range of tools, techniques, and data science methodologies to identify trends and derive meaningful conclusions.
Develop data modeling processes to create algorithms and predictive models, conducting tailored analyses as needed.
Design, build, deploy, and manage the lifecycle of machine learning pipelines.
Collaborate with stakeholders to define and deliver critical insights that drive informed business decisions.
Act as a driving force for innovation in insights generation, aligning efforts with both tactical needs and long-term strategic goals.
Ensure insights are actionable, measurable, and practical, with a clear understanding of their implementation and implications for the business.
Work Experience:
4 to 6 years of practical experience working with data science and analytics tools.
Demonstrated success in leveraging data science methodologies to drive impactful business results.
In-depth expertise in statistical techniques and data mining methods.
Education:
Bachelor’s degree or PhD in an analytical area such as Mathematics, Statistics, Engineering, Machine Learning, Artificial intelligence, or relevant fields with experience in working with AI, ML and Data Science
Knowledge, Skills, Abilities:
Experience with general ML methods and expert in some of the following field:
Recommendation Systems
Supervised learning and feature engineering
Time series and forecasting analysis
Clustering
Significant experience in feature engineering.
Skilled in extracting insights by integrating and analyzing multiple datasets.
Proficient in data science programming languages such as Python or R.
Expertise in machine learning frameworks and libraries like scikit-learn and TensorFlow.
Hands-on experience in designing, deploying, managing, and maintaining machine learning pipelines throughout their lifecycle.
Adept at working with large, distributed datasets to uncover actionable insights.
Logical, systematic thinker with strong teamwork skills, adaptability, and a quick learning ability.
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