Data Analyst (Engineer)

Candidates are to be prescreened and confirmed to have the following mandatory minimum skill sets:

1. Degree in Statistics or Engineering

2. Ability to construct complex SQL queries

3. Ability to manipulate data in R or Python, ideally both

4. Understanding of machine learning algorithms and usage

5. Ability to construct continuously running data pipelines

A Data Analyst is responsible for understanding and deriving insights from the data collected by the company. They would be responsible for maintaining the data and building models from scratch using this data and also tuning and improving existing models as per business requirements.

Depending on the candidate, the candidate can work in Mountain View, Remotely in USA or Canada or any nearshore location.

Degree in statistics, engineering or a related discipline and a passion or expertise in data and statistical analysis.

Understanding of and experience using analytical concepts and statistical techniques: hypothesis development, designing tests/experiments, analyzing data, drawing conclusions, and developing actionable recommendations for business units.

Working knowledge of data mining principles: predictive analytics, mapping, collecting data from multiple data systems on premises and cloud-based data sources.

Experience working in areas such as data warehousing, databases, data visualization, statistics, data analysis, A/B Experiments, reporting, basic machine learning and modeling.

Experience and knowledge of statistical modeling techniques: GLM multiple regression, logistic regression, log-linear regression, variable selection, etc.

Comfortable working with massive unstructured data sets.

Strong SQL skills, ability to perform effective querying involving multiple tables and subqueries.

Expertise in deriving insights from large amounts of data is mandatory

Expertise in customer segmentation, user profiling, and churn analysis is required.

Ability to work with large data sets and to interpret them statistically is expected.

Experience working with and creating databases and dashboards using all relevant data to inform decisions.

Experience using analytics techniques to contribute to company growth efforts, increasing revenue and other key business outcomes.

Strong problem solving, quantitative and analytical abilities.

A least 2 years of experience in monitoring, managing, manipulating and drawing insights from data.

Strong programming skills(Proficiency) with one or more: Python and R, SQL

Experience with big data tools: Bigquery, Pubsub, MapReduce

Experience with data visualization tools: Tableau, DataStudio, d3.js, ggplot.

Optional

Experience using machine learning algorithms, data analytics strong algorithmic thinking and good programming skills will be useful

Experience with Google technologies like Protocol Buffers, Bigtable, Spanner, and Bazel is a huge plus.

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Last updated on Apr 1, 2022