Job Description

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.