Myticas Consulting
Overview
Myticas's direct client is seeking
Data Scientist/Engineer
(100% REMOTE). Duration: 4 Months Contract (Possible further extension). Must-Have Skills Set/Experience
Strong experience in Data Engineering, with big data technologies (Hive, Hadoop, Cloudera, DataIQ). Good in Data Strategies and descriptive analysis. Strong Python Strong SQL Data Science, Statistical methods, machine learning, natural language processing. Work Distribution
50% - Data Engineering, Descriptive Analysis & Data Strategies (manage large datasets, data pipelines, and performing descriptive analytics). 25% - Building Dashboard, and Data visualization 25% - Applying Data Science techniques Job Description
The successful Data Scientist/Engineer will translate business needs into analytic questions; conduct data exploration and model specification; manage data flows and ETL operations; visualize data into dashboards; design and perform analyses of operational, transactional, and log data; and translate these analytic findings into leading information and metrics for our business partners. The chosen candidate would be able to take on responsibilities spanning multiple disciplines across data engineering, data science and analytics programming. Job Responsibilities
Consult with internal and external stakeholders to determine how best to apply analytical solutions that support business objectives Work closely with product managers, analysts, and other stakeholders to provide reliable data deliverables Build and maintain scalable data pipelines. Develop, optimize, and manage ETL processes for structured and unstructured data Ensure data accuracy, integrity, and security across various platforms Implement data quality checks and monitor pipeline performance Collaborate in cloud environments (e.g., AWS, Cloudera, Dataiku, etc.) and with big data technologies (e.g., Spark, Hadoop) Demonstrate a basic knowledge of data science related concepts (i.e. predictive analytics, unsupervised learning, machine learning, deep learning) and how to use them for solving real world problems Adhere to agile project management frameworks and set the direction of data science initiatives Effectively communicate technical concepts to a non-analytic audience Required Qualifications/Experience
Bachelor’s degree in Computer Science, Data Analytics, Engineering, Mathematics, Economics, or related field with ~3 years of relevant professional work experience with an outstanding track record Proficiency in Python and SQL is required. Knowledge of R programming is a plus. Practical experience with data science techniques and toolkits, including times series forecasting, machine learning, deep learning, and LLMs Familiarity with navigating in both a relational (Teradata-based) and non-relational (Hadoop) environment. Knowledge of Java/Scala/Apache Spark is a bonus Practiced in exploratory data analysis (EDA) and manipulating large data sets Good interpersonal skills and ability to present technical concepts to business stakeholders Strong analytical and problem-solving skills Self-starter and intellectually curious with a strong desire to improve business processes through innovation Motivated to gain the full business understanding behind each analytical request
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Myticas's direct client is seeking
Data Scientist/Engineer
(100% REMOTE). Duration: 4 Months Contract (Possible further extension). Must-Have Skills Set/Experience
Strong experience in Data Engineering, with big data technologies (Hive, Hadoop, Cloudera, DataIQ). Good in Data Strategies and descriptive analysis. Strong Python Strong SQL Data Science, Statistical methods, machine learning, natural language processing. Work Distribution
50% - Data Engineering, Descriptive Analysis & Data Strategies (manage large datasets, data pipelines, and performing descriptive analytics). 25% - Building Dashboard, and Data visualization 25% - Applying Data Science techniques Job Description
The successful Data Scientist/Engineer will translate business needs into analytic questions; conduct data exploration and model specification; manage data flows and ETL operations; visualize data into dashboards; design and perform analyses of operational, transactional, and log data; and translate these analytic findings into leading information and metrics for our business partners. The chosen candidate would be able to take on responsibilities spanning multiple disciplines across data engineering, data science and analytics programming. Job Responsibilities
Consult with internal and external stakeholders to determine how best to apply analytical solutions that support business objectives Work closely with product managers, analysts, and other stakeholders to provide reliable data deliverables Build and maintain scalable data pipelines. Develop, optimize, and manage ETL processes for structured and unstructured data Ensure data accuracy, integrity, and security across various platforms Implement data quality checks and monitor pipeline performance Collaborate in cloud environments (e.g., AWS, Cloudera, Dataiku, etc.) and with big data technologies (e.g., Spark, Hadoop) Demonstrate a basic knowledge of data science related concepts (i.e. predictive analytics, unsupervised learning, machine learning, deep learning) and how to use them for solving real world problems Adhere to agile project management frameworks and set the direction of data science initiatives Effectively communicate technical concepts to a non-analytic audience Required Qualifications/Experience
Bachelor’s degree in Computer Science, Data Analytics, Engineering, Mathematics, Economics, or related field with ~3 years of relevant professional work experience with an outstanding track record Proficiency in Python and SQL is required. Knowledge of R programming is a plus. Practical experience with data science techniques and toolkits, including times series forecasting, machine learning, deep learning, and LLMs Familiarity with navigating in both a relational (Teradata-based) and non-relational (Hadoop) environment. Knowledge of Java/Scala/Apache Spark is a bonus Practiced in exploratory data analysis (EDA) and manipulating large data sets Good interpersonal skills and ability to present technical concepts to business stakeholders Strong analytical and problem-solving skills Self-starter and intellectually curious with a strong desire to improve business processes through innovation Motivated to gain the full business understanding behind each analytical request
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