Data Analytics Specialist - Remote / Telecommute

Cynet Systems; Edmonton (KY); Remote; USD 80,000 - 110,000; Full time

Job summary

A leading company in data analytics is seeking a Data Scientist to drive strategic data initiatives. The ideal candidate will have extensive experience in data analytics, statistical modeling, and programming. Responsibilities include analyzing data, building predictive models, and collaborating with stakeholders to enhance data-driven decision-making. This role requires strong leadership skills and a client-centric approach to foster innovative solutions.

Qualifications

• 6 years of experience with statistical and programming languages.
• Experience in building analytical and quantitative models.
• Knowledge of various data analytics and data science approaches.

Responsibilities

• Coordinate with clients to understand analytics needs.
• Analyze raw data and build algorithms for business value.
• Coach and mentor team members in data analytics.

Skills

Data Analytics

Machine Learning

Statistical Modeling

Data Visualization

Programming

Education

Bachelor's degree in Computer Science

Tools

R

Python

SQL

Hadoop

Spark

Azure

Snowflake

Job description

Provides hands-on support, leadership, advice, and direction on the strategic data initiatives that are being undertaken as part of the Data Strategy.

1. Coordinate with internal and external clients to understand their analytics needs and how to best utilize data to meet these needs.
2. Anticipate, identify, and respond to complex data analytic requirements across client departments and external organizations, aligning with broader department goals.
3. Ensure services and project deliverables evolve with emerging user and business needs, as well as design and technical opportunities.
4. Collaborate with the Manager of Analytics Capability Centre to:

• Provide expertise and leadership in designing and executing analytic projects.
• Develop and share data models and products.
• Improve analytics capacities continuously.
• Design and support analytic service offerings.

Analyze raw data, prepare it for modeling, and build algorithms to deliver business value.

Evaluate business needs, enhance data quality, and design analytical tools.

Conduct complex data analyses and collaborate with data engineers and analysts.

Coach and mentor team members, fostering a client-centric approach and innovative solutions.

Support senior management in shifting toward data as a strategic asset and maintain stakeholder relationships.

Create and present options, roadmaps, frameworks, models, and briefings for senior executives.

Facilitate strategic conversations to develop shared understanding and decision-making options.

Develop baseline and ongoing outcomes, metrics, and indicators.

Extract knowledge from data using various techniques, including machine learning, statistics, and data visualization.

Apply skills in Data Analytics or as a Data Scientist to support decision-making and strategic planning.

Focus on predictive and needs-based analytics strategies to produce reusable analytical models that generate measurable value.

Provide insights into operations, transactions, and services to identify new opportunities through analytics.

Transform data assets into meaningful analytics for decision-making.

Utilize statistical classification techniques such as k-means, hierarchical clustering, and logistic regression.

Integrate quantitative and qualitative data to create business insights.

Design and create dashboards and custom reports from various data sources.

Gather and document client requirements and metadata for analytical products.

Escalate issues and risks appropriately.

Work within a multi-vendor/staff environment with specific deliverables and due dates.

Provide weekly and monthly status reports.

Must Have:

• Bachelor's degree in Computer Science or related field; equivalencies considered.
• 6 years of experience with statistical and programming languages like R, Python, SQL.
• 6 years of experience in building analytical and quantitative models.
• 6 years of experience with data science, data engineering, or AI projects.
• 6 years of experience in preparing data for modeling.
• 6 years of experience understanding complex business questions and framing analytical problems.
• Knowledge of various data analytics and data science approaches, including complex statistical modeling.
• Understanding of statistical and data mining techniques addressing key business issues.

Nice to Have:

• Experience with data sharing, data-linkage, de-identification, metadata, data quality, ethics, synthetic data, and data literacy.
• Experience combining raw data from multiple sources.
• Experience explaining complex data principles to clients.
• Designing and maintaining data pipelines and workflows.
• Preparing visualizations, dashboards, and analytical models.
• Developing requirements for analytical projects.
• Experience with big data technologies (e.g., Hadoop, Spark) or cloud platforms (Azure, Snowflake).
• Experience working with large government datasets.