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Capillary Technologies

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3.5

based on 190 Reviews

Video summary

1 Capillary Technologies Data Science Associate Job

Associate Data Science

Capillary Technologies India Pvt. Ltd.

3.5

based on 190 Reviews

2-5 years

₹ 7.632 - 8L/yr (AmbitionBox estimate)

Bangalore / Bengaluru

1 vacancy

Associate Data Science

Capillary Technologies

posted 25d ago

Job Role Insights

Flexible timing

Key skills for the job

Data Science Python SQL Machine Learning Recruitment Tableau

+ 2 more

Job Description

The Data Science Associate is responsible for supporting the data science team in developing, implementing, and maintaining data-driven solutions that support business objectives. This includes working with large datasets, developing data models, and analyzing data to provide insights and recommendations.

Key Responsibilities:

Collaborate with the data science team to identify business needs and develop data-driven solutions to address them.
Collect, clean, and preprocess large and complex data sets from various sources.
Develop statistical models and predictive models to identify patterns and trends in data.
Analyze data to identify insights and opportunities for business improvement.
Communicate findings and recommendations to key stakeholders in a clear and concise manner.
Use data visualization tools to communicate complex data in an easy-to-understand format.
Stay up-to-date with industry trends and new developments in data science.

Qualifications:

Bachelors or Masters degree in computer science, statistics, mathematics, or related field.
Strong programming skills in languages such as Python or R.
Experience with data manipulation and analysis tools such as SQL and Excel.
Knowledge of statistical modeling and machine learning techniques.
Familiarity with data visualization tools such as Tableau or Power BI.
Excellent problem-solving and analytical skills.
Strong communication and collaboration skills.

Programming: Proficiency in at least one programming language such as Python, R or SQL is essential. They should be able to write and understand code, manipulate and analyze data, and be familiar with common data structures and algorithms.
Statistics and Mathematics: A solid understanding of statistics and mathematics is important for data science. This includes knowledge of probability theory, statistical inference, and basic linear algebra.
Data wrangling: Data wrangling involves cleaning, transforming, and merging data from different sources. A data scientist should be proficient in using tools such as pandas, dplyr or SQL to manipulate and preprocess data.
Machine Learning: Familiarity with machine learning concepts such as supervised and unsupervised learning, regression, classification, and clustering is important. They should be able to build basic models and evaluate their performance.
Data Visualization: Data visualization is an important skill for a data scientist. They should be able to create visualizations that communicate insights and findings to both technical and non-technical stakeholders. Familiarity with tools such as matplotlib, ggplot or Tableau is valuable.
Communication and problem-solving: Strong communication skills are important for a data scientist to explain their findings and insights to stakeholders. They should also possess problem-solving skills and be able to identify and frame problems in a data-driven manner.

It has been brought to our attention that there have recently been instances of fraudulent job offers, purporting to be from Capillary Technologies. The individuals or organizations sending these false employment offers may pose as a Capillary Technologies recruiter or representative and request personal information, purchasing of equipment or funds to further the recruitment process or offer paid training. Be advised that Capillary Technologies does not extend unsolicited employment offers. Furthermore, Capillary Technologies does not charge prospective employees with fees or make requests for funding as a part of the recruitment process.

We commit to an inclusive recruitment process and equality of opportunity for all our job applicants.

Employment Type: Full Time, Permanent

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