[Hiring] Data Scientist @Improvix Technologies

Role Description

The Data Scientist will design, develop, and operationalize advanced analytics solutions that drive data‑informed decision‑making across the organization. This role blends statistical modeling, data engineering, and visualization skills to turn complex datasets into actionable insights. The position will work across the full analytics process, including data preparation, transformation, modeling, validation, reporting, and production support. The ideal candidate is comfortable working with large datasets, solving complex data problems, and partnering with both technical teams and business users. This is a fully remote position.

Key Responsibilities

• Build scalable data pipelines and analytics workflows using Databricks (PySpark, Delta Lake, notebooks).
• Develop interactive dashboards and reports in Power BI, ensuring strong usability, accuracy, and performance.
• Build and maintain Power BI data models and DAX measures to support reporting and analytical needs.
• Work with large and complex datasets and identify ways to improve query performance, processing time, and overall efficiency.
• Partner with business stakeholders to translate analytical needs into technical solutions.
• Perform exploratory data analysis, feature engineering, and model development using machine learning techniques.
• Optimize data models for reliability, governance, and reusability across teams.
• Collaborate with engineering teams to deploy analytics products into production environments.
• Document processes, data definitions, and system logic for transparency and maintainability.
• Support the team's active data migration from Splunk to Databricks, working across both platforms as needed.
• Build and maintain API integrations with external platforms, including OAuth 2.0 authentication and token management, to support data ingestion.

Qualifications

• Strong proficiency in Power BI for data modeling, DAX, report development, and visualization best practices.
• Strong experience with Databricks and distributed data processing (Spark).
• Advanced SQL skills with experience querying, transforming, and optimizing large datasets.
• Strong Python skills for data analysis, transformation, automation, and analytics.
• Power Automate experience for building workflow automations; this is a core day-to-day tool for the team.
• Experience building and maintaining data pipelines and working with modern data architectures.
• Understanding of cloud data platforms and architectures, preferably Microsoft Azure.
• Strong presentation skills, with the ability to speak conversationally about projects, findings, and solutions rather than reading from slides, and to adjust technical depth for both highly technical stakeholders and non-technical leadership.
• Strong analytical mindset with the ability to interpret data trends and communicate clearly.
• Experience collaborating in cross‑functional environments and managing competing priorities.
• Ability to adapt solutions and problem solve using the tools available.

Preferred / Bonus Skills

• Experience using JIRA for task management and reporting.
• Familiarity with CI/CD workflows, DevOps practices, or automation tools.
• Exposure to API integrations (including OAuth 2.0 authentication and token cycling), data governance frameworks, or DataOps methodologies.
• Exposure to UiPath or other RPA platforms, and familiarity with ServiceNow for accessing hardware and other operational datasets.
• Strongly preferred: experience with Splunk (search, log analysis, operational analytics, or dashboard development). The team is in the middle of migrating from Splunk to Databricks, so comfort moving between both platforms is a significant plus.
• Interest or experience applying AI tools within analytics workflows (e.g., Power Automate AI Builder or similar AI-assisted platforms); the team is actively looking to expand AI adoption.

Education & Experience

• Bachelor’s degree in Data Science, Computer Science, Statistics, Information Systems, or related field preferred, but not required for candidates with strong relevant experience.
• 3+ years of experience in analytics, data engineering, or data science roles (or equivalent practical experience).
• Active Secret clearance required; candidates already holding a Secret may be considered for sponsorship to a higher-level clearance.

Success Criteria

• Deliver high-quality dashboards and analytics with measurable business impact.
• Improve data accessibility and reliability through well‑structured models and pipelines.
• Act as a trusted advisor for stakeholders seeking data‑driven insights.
• Maintain confidence in reporting through strong validation, documentation, and data quality practices.

Benefits

• Competitive compensation and performance-based incentives.
• 401(k) with company match.
• Three weeks of paid annual leave that increases with tenure.
• Comprehensive medical, dental, and vision insurance.
• Life insurance and disability coverage.
• Transit and commuting benefits.
• Professional development and paid training opportunities.