HexaQuEST Global, Inc.
Data Scientist Expert
HexaQuEST Global, Inc., New York, New York, us, 10261
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.
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.