Data Analyst (Client Facing)

The Data Analyst is a part of the Customer Success team, which is responsible for all of our clients, starting from the POC stage and through deployment in production environments. The CS team assists our clients in the design, planning, and implementation of predictive analytics programs. We are looking for an enthusiastic and client-focused data analyst.

What You'll Do

As a data analyst at Pecan, you will work at the forefront of the data world, by creating and optimizing predictive models and assisting our clients to use those predictions to affect their business and generate value.

Together with the team, you will be continuously helping our clients achieve their business goals and reinforce the value of Pecan. You'll assist in covering data and technical aspects of integrating clients’ systems with our predictive analytics platform.

Typical tasks of the position are:

• Collaborate with the client's business stakeholders, gather technical requirements, and understand the need for predictive models.
• Analyze large volumes of data sets using different coding languages as SQL and Python.
• Analyze the model’s outputs and explain complex concepts in simple words.
• Collaborate with clients’ teams and translate business needs to data solutions.
• Be the data and technical point of contact for our clients, and understand their needs.
• Develop tools and data research to improve the quality of predictions.

Who You Are & What You Bring:

• 1-2 years of work experience as a data analyst
• 1+ years of experience in SQL, python (Pandas, Numpy)
• Demonstrated experience in problem-solving and providing business insights
• Excellent business analytical skills
• Great attitude & team player
• Excellent English
• BA/BS in Engineering, Statistics/Math, Economics, or a related field

Nice to Have:

• Experience with cloud data warehouse technologies (AWS, Snowflake, BigQuery, etc.)
• Experience with data visualization tools and methodologies.
• Familiarity with predictive analytics and modeling processes
• Statistical experience (creating attribution models, A/B tests, or lift analysis)