As a Data Scientist with a Ph.D., this role will be multifaceted, involving advanced data analysis, statistical modeling, and algorithm development. Person will be responsible for deriving insights from complex datasets, guiding decision-making processes, and driving innovation within the organization.
Responsibilities:
Data Analysis and Exploration:
- Utilize advanced statistical techniques to analyze large datasets and extract actionable insights.
- Develop algorithms and models to identify patterns, trends, and correlations within the data.
Statistical Modeling:
- Design and implement predictive models using machine learning algorithms such as regression, classification, clustering, and time series analysis.
- Validate models for accuracy, reliability, and robustness.
Algorithm Development:
- Develop and optimize algorithms for data mining, feature extraction, and anomaly detection.
- Collaborate with cross-functional teams to deploy algorithms into production systems.
Research and Development:
- Stay abreast of the latest advancements in data science, machine learning, and related fields.
- Conduct research to explore novel approaches and techniques for solving complex data-related problems.
Data Visualization and Communication:
- Present findings and insights to stakeholders using compelling data visualizations, reports, and presentations.
- Collaborate with business teams to translate analytical findings into actionable recommendations.
Data Governance and Ethics:
- Ensure compliance with data governance policies and regulations.
- Uphold ethical standards in data collection, analysis, and usage.
Qualifications:
- Ph.D. in Computer Science, Statistics, Mathematics, Engineering, or a related field.
- Strong background in statistical analysis, machine learning, and data mining techniques.
- Proficiency in programming languages such as Python, R, or Julia.
- Experience with data manipulation and visualization tools like SQL, Pandas, Matplotlib, and Tableau.
- Ability to work with large-scale datasets and distributed computing frameworks such as Hadoop, Spark, or Dask.
- Excellent communication and collaboration skills, with the ability to convey complex technical concepts to non-technical stakeholders.
- Strong problem-solving skills and a passion for tackling real-world challenges using data-driven approaches.
Additional Preferred Skills:
- Experience with deep learning frameworks such as TensorFlow or PyTorch.
- Knowledge of cloud computing platforms such as AWS, Azure, or Google Cloud Platform.
- Familiarity with big data technologies such as Kafka, Hive, or Cassandra.
- Experience in specific domain areas such as healthcare, finance, e-commerce, or telecommunications.