Job Description
Staff-level Data Scientist
Responsibilities :
- Lead end-to-end data science projects, including problem formulation, data collection,
cleaning, feature engineering, model development, validation, and deployment.
Apply advanced statistical analysis, machine learning algorithms, and data mining techniquesto extract insights and patterns from large-scale structured and unstructured data sets.
Collaborate with stakeholders to define project objectives, deliverables, and success metricsaligned with business goals.
Develop and maintain scalable and efficient data pipelines, ensuring data integrity, quality, andsecurity.
Implement and optimize machine learning models, deep learning architectures, and otherstatistical techniques to solve complex business problems.
Design and conduct rigorous experiments, A / B tests, and statistical hypothesis tests tomeasure the effectiveness of data-driven solutions.
Communicate complex analytical findings and insights to both technical and non-technicalstakeholders through visualizations, presentations, and reports.
Stay up-to-date with the latest advancements in data science, machine learning, and relatedtechnologies, and apply them to improve existing processes and methodologies.
Provide guidance, mentorship, and technical leadership to junior data scientists, fostering acollaborative and knowledge-sharing culture within the team.
Requirements :
Bachelor's or advanced degree in Computer Science, Statistics, Mathematics, or a relatedquantitative field.
Minimum of 8 years of professional experience as a Data Scientist, with a proven track recordof delivering impactful data-driven solutions.
Expertise in machine learning techniques such as regression, classification, clustering, timeseries analysis, natural language processing, and recommendation systems
Proficiency in programming languages such as Python, R, or Scala, along with experienceworking with libraries and frameworks like scikit-learn, TensorFlow, PyTorch, or Keras.
Solid understanding of statistical analysis, experimental design, and hypothesis testing.Experience with big data technologies (e.g., Hadoop, Spark) and working with large-scale datasets.
Strong data manipulation and SQL skills, along with proficiency in data visualization tools likeTableau, Power BI, or matplotlib.
Demonstrated ability to lead and manage complex data science projects, including projectscoping, planning, and execution.
Excellent problem-solving and critical-thinking skills, with a keen attention to detail and apassion for tackling challenging analytical problems.
Strong communication skills, with the ability to translate complex technical concepts into clearand concise insights for stakeholders at various levels of the organization.
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