Data Scientist Expert

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 decisionmaking 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 crossfunctional 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 datarelated 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 largescale 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 nontechnical stakeholders.
Strong problemsolving skills and a passion for tackling realworld challenges using datadriven 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 ecommerce or telecommunications.