Data Science Analyst

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Luxoft

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Job Summary


Job Type
-

Seniority

Years of Experience
Information not provided

Tech Stacks
Python NumPy Pandas Sas Matplotlib R API seaborn

Job Description

Project Description:

We are looking for a detail-oriented and driven Data Science Analyst to join our team. The successful candidate will use their skills in Python, data analysis, and data visualization to turn data into information, information into insight, and insight into business decisions. This role will operate with a broad remit across multiple accounts and will have extensive opportunities to explore insights across multiple service lines / customers. The DXC team is passionate about data science and insights - we are equally looking for a passionate analyst with a genuine interest in continuous improvement and innovation. Opportunities will exist to present data to senior stakeholders and engage in business facing discussion.


Responsibilities:

• Interpret data and analyze results using statistical techniques.

• Develop and implement data collection systems and other strategies that optimize statistical efficiency and data quality.

• Identify, analyze, and interpret trends or patterns in complex data sets.

• Work closely with management to prioritize business and information needs.

• Locate and define new process improvement opportunities.


Mandatory Skills Description:

Qualifications:

Proven working experience as a Data Analyst or Business Data Analyst.

Strong knowledge of and experience with Python.

Knowledge of statistics and experience using statistical packages for analyzing datasets.

Strong analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy.

Experience with data visualization tools and techniques.

Adept at queries, report writing and presenting findings.

BS in Mathematics, Economics, Computer Science, Information Management or Statistics.


Skills:

Python: Proficiency in Python is a must. Experience with data science libraries like pandas, numpy, and scikit-learn is highly desirable.

Data Visualization: Experience with data visualization tools such as Matplotlib, Seaborn, or Tableau. Ability to present complex data in a clear and concise manner.

Statistical Analysis: Strong background in statistical concepts and calculations with experience in using statistical languages, such as R or SAS.

Machine Learning: Familiarity with machine learning algorithms and concepts.

Communication Skills: Ability to translate complex findings and insights into understandable visual representations and reports.

Problem-Solving: Strong problem-solving skills to provide solutions for business needs

Data management: API, database and other supporting technologies necessary to deliver outcomes.


Languages:

English: C2 Proficient


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