Data Scientist

JANA has a progressive culture of personal and professional growth. With a vested interest in each employee’s professional growth and continuous improvement as an individual, JANA supports professional development, continuous education, industry participation and technical accreditations. Other Perks that come with joining the JANA Family include:

- High-energy Collaborative Environment: JANA combines the energy of a start-up software organization with the discipline of a precision engineering firm.
- Regular Social Events: Join the entire JANA Team for fun online Social Events like our Weekly Kahoot and Beer Clubeven an Easter Egg Hunt We also like to get together for in-person events such as our Annual Birthday Bonspiel, Ice Cream Parties, Holiday events, and our annual Company Picnic
- Best-in-Class Benefits: JANA offers all employees a comprehensive benefits package including Medical, Dental, Vision, Life Insurance, AD&D, Disability coverage, as well as our great Wellness Benefit JANA also provides employees with the opportunity to get support with mental wellness, through our great Employee Assistance Program.
- Giving Back: JANA is dedicated to giving back to our community. We hold an annual food drive for the Aurora Foodbank and have become one of their top contributors
- JANA promotes a healthy work-life balance: Through our comprehensive vacation program, floater days, and a hybrid work environment, JANA employees are able to take time to rest and rejuvenate

DELIVERY DATA SCIENTIST

Without a strong team of dedicated, driven, talented, and professional employees, JANA will not be able to reach our north star of Unmatchable Client Experience. JANA’s Delivery Data Scientist is responsible for acquiring and preparing client data for risk modelling and collaborating with the project team to provide clients with essential insights to help them understand risk analysis and improve their source data for future modelling. This process is core to the success of JANA’s client implementations.

JANA’s Delivery Data Scientist is excited by solving challenging business problems and optimizing processes, and

improving data preparation processes based on the needs of each project.

Reporting to the Delivery Manager, the Delivery Data Scientist, provides the large data set statistical analysis, identifying trends, and ensures data quality.

**Responsibilities**:

- Data Pipeline: Adopt and optimize data pipeline and ETL (Extract, Transform, Load) processes to efficiently move and transform data from various sources into structured formats for storage and analysis.
- Data Analysis: Extract, clean, and preprocess large volumes of structured and unstructured data from various sources, ensuring data quality and integrity.
- Data Visualization: Present findings and insights through visually compelling dashboards, reports, and presentations, enabling stakeholders to grasp complex information easily and make data-driven decisions.
- Collaborative Problem Solving: Collaborate with cross-functional teams, including data engineers, and business analysts, to understand business requirements, define problem statements, and develop analytical solutions.
- Continuous Improvement: Stay up-to-date with the latest advancements in data science, machine learning, and statistical modeling techniques, and proactively identify opportunities to enhance existing processes and methodologies.
- Communication and Stakeholder Management: Effectively communicate complex findings and technical concepts to non-technical stakeholders, fostering a data-driven culture and promoting the value of data science within the organization.

Required Skills & Experience
- Education: Bachelor's degree in Computer Science, Statistics, Mathematics, or a related field
- Data Scientist Experience: Minimum 1 year experience in data science.
- Technical Skills: Strong programming Proficiency in Python, along with experience using data manipulation and analysis libraries (e.g., Pandas, NumPy, SciPy). Strong knowledge of SQL for data extraction and manipulation. Familiarity with data visualization tools like Tableau, Power BI, or matplotlib.
- Data Manipulation and Analysis: Ability to work with large, complex datasets, perform data cleaning, feature engineering, and exploratory data analysis (EDA). Experience with GCP and big data technologies like Hadoop or Spark is a plus.
- Communication and Collaboration: Excellent verbal and written communication skills to effectively convey complex findings and insights to both technical and non-technical audiences. Demonstrated ability to collaborate and work in cross-functional teams.
- Business Acumen: Understanding of business processes and the ability to translate business requirements into data-driven solutions. Experience in specific domains (e.g., finance, healthcare, e-commerce) is a plus.
- Continuous Learning: Strong motivation to stay updated with the latest advancements in data science, machine