Company Description
Are you looking for an opportunity to jump-start your career in a thriving tech industry? Join us at Blend to grow our business and execute our mission to help organizations leverage data and technology to make better decisions. With over 10 years of experience in the field of big data, top US customers such as Mastercard, CVS, and Roku choose us to develop innovative products.
What is This Position About?
As a Data Scientist, you will play a pivotal role in our data-driven journey. Your focus will be on analyzing customer purchase patterns, identifying trends, and uncovering insights to enhance our understanding of customer behaviors.
This role offers the opportunity to work independently on challenging projects while collaborating with a diverse global team.
You may work 100% remotely if you are currently living in LATAM or you can always join us at the office in Montevideo, Uruguay!
Job Description
- Utilize SQL, Python, and potentially Spark for extracting, transforming, and analyzing large datasets.
- Perform data mining and utilize statistical modeling techniques to generate actionable insights from complex, high-dimensional data.
- Create visually appealing data visualizations (graphs, tables, dashboards) to effectively communicate findings and recommendations to stakeholders.
- Independently manage and execute projects aimed at deepening our understanding of customer preferences and behaviors.
- Collaborate closely with stakeholders, including daily sync-ups with international teams, particularly with Queenie, to prioritize and strategize ongoing investigations.
- Engage in code review and programming tasks to ensure data analysis processes are efficient and accurate.
- Contribute to long-term projects focusing on customer analytics and behavior patterns in the retail sector.
Qualifications
- Bachelor's degree in Computer Science, Statistics, Mathematics, or a related field; Master's degree preferred.
- Proficiency in SQL for data manipulation and extraction.
- Strong programming skills in Python, with experience in libraries like Pandas, Scikit-learn, and familiarity with Jupyter notebooks.
- Ability to work with big data technologies and frameworks (e.g., Spark) is a plus.
- Experience in statistical modeling techniques such as supervised/unsupervised learning, variable importance, experimentation, and causal modeling.
- Skilled in data visualization tools and techniques to create compelling visual narratives.
- Excellent communication skills to articulate complex findings and recommendations to non-technical stakeholders.
- Background in retail analytics or similar industry experience is a significant advantage.
- Ability to work asynchronously in a collaborative team environment across global locations.
What about languages?
- You will need excellent written and verbal English for clear and effective communication with the team.
How much experience must I have?
- We're looking for someone with 3+ years' of experience in similar roles.
Additional Information
Our perks and benefits:
🍔Every day lunches! (headquarters)
- Vegetarian, vegan, gluten and sugar-free options.
- Gourmet meals every Friday with our on-site chef!
⚖️ Flexible working options to help you strike the right balance.
👨🏽💻 All the equipment you need to harness your talent (Macbook and accessories).
☕Snacks and beverages available everyday (headquarters).
🎮After office events, football, tennis and game nights (headquarters).
- Everyone is welcome to join our football league every Wednesday’s and Friday’s.
- Challenge your teammates to a pool game and win the office’s trophy!
- Tennis courts available for friendly matches.
- You are not a sports person? Don’t worry, we also have chess championships, game and music nights for you to join!
📚 Learning opportunities:
- AWS Certifications (we are AWS Partners).
- Study plans, courses and other certifications.
- English Lessons.
- Learn from your teammates on our Tech Tuesdays!
👩🏫 Mentoring and Development opportunities to shape your career path.
🎁 Anniversary and birthday gifts.
🏡 Great location and even greater teammates!
So what are the next steps?
We are eager to learn about you! Send us your resume or LinkedIn profile below and we’ll explore working together!