Data Science analyst

Data Science Analyst

Partner with clients to develop strong understanding of business needs and use business understanding to help design effective analytical solutions.

Perform all data preparation and exploratory data analysis steps.

Apply common statistical methods, data modeling to answer strategic questions for the business.

Mine complex digital behavioral data, unveil insights and transform it into actionable information.

Conduct quantitative data analysis using a variety of large structured and unstructured datasets including developing retrieval, processing, fusion, analysis, and visualization of various datasets.

Identify and test hypotheses, ensuring statistical significance, as part of building predictive models for business application.

Translate findings into succinct, actionable business insights, and coordinate with technical/ business partners to prepare holistic story.

Use advanced data visualization techniques to communicate solutions to business stakeholders.

Guide implementation, testing, and evaluation of models.

Present methodology and findings of analysis to a broad range of audiences, including both technical and non-technical, at all levels of the organization.

Enable business to make clear tradeoffs between and among choices, with a reasonable view into likely outcomes.

Collaborate closely with other members of the analytics and data science team and the Harman data science community.

Articulate complex ideas clearly to a nontechnical business audience.

Manage and control changes & scope.

Lead analysis, design, development, implementation, and post implementation phases of data science modules.

Lead work progress and address any questions or challenges regarding projects. Own progress reporting.

Lead planning, execution, and delivery of data science modules within program.

Identify risks, gaps, and opportunities and communicate to stakeholders and other teams to drive resolution

Master’s degree or higher in Computer Science, Data Science, Engineering, Mathematics, Statistics, or related field.

Advanced understanding of probability, statistics, machine learning, data science.

Expertise in data correlation/feature analysis, analysis of machine learning models, and optimizing models for accuracy.

Proficiency in transforming and cleaning data & working across multiple models.

Ability to research and manipulate complex and large data sets (both distributed and non-distributed).

Strong ability to synthesize complex information.

3+ years’ experience in Python, Scala, Power BI, Excel, or similar.

Excellent knowledge of anomalies/outliers detection using unsupervised algorithms – clustering, Local Outlier Factor, Isolation Forest, etc.

Strong written and verbal communication skills.

Experience in stakeholder management.

Experience in leading cross geography data science teams.