Junior Data Scientist

3 weeks ago

Pleasanton, United States Flexon Technologies Full time

Job Description

Job Description

Job Summary: We are seeking a talented and motivated Junior Data Scientist to join our data analytics team. As a Junior Data Scientist, you will work on various data projects, assisting in data analysis, modeling, and developing machine learning solutions. You will collaborate with senior data scientists and cross-functional teams to extract insights from data and contribute to data-driven decision-making. The ideal candidate should have a strong foundation in data science concepts, programming skills, and a passion for solving complex problems using data. Qualifications: · Bachelor's or Master's degree in Data Science, Computer Science, Statistics, or a related field. · Strong understanding of data science concepts, statistical analysis, and machine learning algorithms. · Proficiency in programming languages such as Python ( 1 to 2 Years) or R ( 1 to 2 Years) for data manipulation, analysis, and modeling. · Familiarity with data visualization tools and libraries, such as Matplotlib or Tableau. · Experience with data preprocessing, feature engineering, and data cleaning techniques. · Basic knowledge of SQL for data querying and manipulation. · Strong problem-solving skills and ability to think analytically. · Excellent communication skills, with the ability to effectively present complex concepts and findings to non-technical stakeholders. · Ability to work collaboratively in a team environment and contribute to team goals. · Knowledge of cloud platforms, such as AWS or Azure, and experience working with big data technologies are desirable. · Familiarity with version control systems like Git and knowledge of software development practices is a plus · Basic Understanding of Machine Learning Operations (MLOps): Familiarity with the lifecycle of machine learning models from development to deployment and maintenance. · Knowledge of Data Ethics and Privacy: Understanding of data privacy laws (like GDPR) and ethical considerations in data science. · Adaptability to New Technologies: Ability to quickly learn and adapt to new data analysis tools and techniques as they emerge. · Critical Thinking: Ability to approach problems critically and propose innovative solutions. · Project Management Skills: Basic project management skills to manage tasks efficiently and meet deadlines.

Responsibilities: · Assist in data collection, preprocessing, and cleaning to ensure data quality and usability for analysis. · Perform exploratory data analysis to identify patterns, trends, and relationships in the data. · Develop and implement statistical and machine learning models to solve business problems. · Collaborate with senior data scientists to design and execute experiments, analyze results, and generate actionable insights. · Conduct data visualization to effectively communicate findings and present insights to stakeholders. · Assist in developing and maintaining data pipelines and workflows for data ingestion, transformation, and analysis. · Stay abreast of the latest data science techniques, tools, and methodologies, and apply them to enhance analytics capabilities. · Collaborate with data engineering and IT teams to ensure seamless integration and availability of data for analysis. · Contribute to the development and improvement of data science workflows and best practices. · Document and communicate the methodology, assumptions, and limitations of data models and analyses. · Assist in Model Deployment: Aid in deploying machine learning models into production environments, ensuring they run efficiently and reliably. · Participate in Code Reviews: Engage in code review processes to ensure quality and adherence to best practices. · Data Quality Assurance: Regularly check data sources for integrity and accuracy.

· Continuous Learning: Commitment to continuous learning and staying updated with advancements in data science and related fields.

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