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 Client 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.