: Data Science & Analytics Manager

If you ever wanted to be on the ground floor of a well-funded, rapidly growing Series C start-up that is disrupting a 5.7Tn market, now is the time to join Takeoff Technologies! We are a 250 person global company transforming online grocery for consumers & retailers. Takeoff's solution offers automated fullfillment coupled with an end-to-end e-Grocery technology stack, enabling retailers to offer their shoppers the assortment and low prices of stores, with convenient mobile ordering and same day pickup or delivery.


Our eGrocery solution was created with the grocer and the shopper in mind. Grocery is an incredibly complex industry, and our products are unlike any other: they are low value, perishable, heavy, and low-margin. Our automated solution is flexible enough to manage these complexities allowing us to ensure the correct picking method for the correct product!


Excited about potentially joining this rocketship to help us bridge the gap between retail and technology? Looking to make an impact daily and help us disrupt a hundred year old industry? If so, continue reading!


Data Science and Analytics Manager (Takeoff Technologies, Inc.; Waltham, Massachusetts): Takeoff provides automated fulfillment coupled with an end-to-end eGrocery solution. The Data Science and Analytics Manager is responsible for leading a team of data scientists, data engineers and data analysts to:

(a) Produce models that can be scaled by the software development teams which enable self-serve analytical capabilities. Will also unlock value from data using Data Science techniques including Machine Learning, Deep Learning and Natural Language Processing to help guide the business everything from tactical optimizations to broad level strategic direction that is grounded in data evidence and heavy analytical rigor.

(b) Design, build and own the big data infrastructure, data pipeline and analytics platform including Data Lake, Data Warehouse and Business Intelligence (BI) tools. Will also build stable, automated and scalable solutions to make data available, accessible and usable by all teams in the company in order to help drive the direction of products.


Specific responsibilities will include:

Responsible for defining the teams roadmap and executing against it in close collaboration with Engineering, Operation, and Product Managers. Own the full Data Science life-cycle from initial conception to prototyping, testing, deploying, scaling and measuring its overall business value.

Define, build and develop high-performing teams of experienced data scientists and data analysts to deliver world-class products. Coach and continuously drive them to achieve higher level of excellence.

Work and deliver end-to-end projects independently including ability to lead teams to quickly adapt to changing priorities and generate innovative solutions in an extremely fast-paced environment.

Build and evolve models in a test and learn fashion within an Agile environment.

Proactively drive the vision for Data Warehousing and BI across a product vertical and define and execute on a plan to achieve that vision. Responsible for Strategic Data Warehouse Initiative. Work closely with all business units to develop long term data platform architecture including plan, budget, and execution.

Manage the teams that own the complete data pipeline, from data warehouse import all the way through to end-user BI tools. Work with the Integration team to ensure required data is staged via ETL (extract, transform, load) jobs in a way that makes it usable to influence business decisions.

Be a thought leader on data systems, data mining and analysis to scale our capabilities, uncover trends, and develop insights.

Ensure and continuously improve data integrity, data accuracy, and data quality.

Get hands-on with large disparate datasets, hack through complex and messy data, and analyze it leveraging the latest algorithms and state-of-the-art techniques and tools. Translate vast amounts of data in raw formats (both structured and unstructured data) into digestible information for stakeholders to use for actionable strategies.

Oversee the building and maintaining of reports, dashboards, and metrics to monitor the performance of our products.

Work with executives and stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions and help determine the strategic direction of the company. Size opportunities to ensure product teams are prioritizing the most impactful work.

Partner with Product and Engineering teams to solve problems. Increase adoption of data products across business partners, to drive real business value.

Responsible for prototype solutions, mathematical models, algorithms, machine learning techniques, and robust analytics to provide insights and development of data products.

Lead a team that applies state of the art Machine Learning, Deep Learning and Natural Language Processing techniques to understand and transform how users interact with our core products.

Oversee the algorithm development process, focusing on fast model iteration and testing to measure and evaluate success. Implement Machine Learning and Deep Learning models into production by collaborating with Product and Engineering teams.

Develop standardized code and processes that can be easily used by the larger team.

Inform, influence, support, and execute our product decisions.

Research new technologies and methods across data science, data engineering, and data visualization to improve the technical capabilities of the team.

Communicate research, findings and model results clearly and effectively to a wide audience of relevant partners, and build meaningful presentations and analyses that tell a story.

Prepare client facing material including PowerPoint slides and charts, distilling analytical insights effectively into stories for clients.

Minimum Requirements: Masters degree in Statistics, Computer Science, Mathematics, Physics, Operations Research, or another highly quantitative or STEM field and 5 years of hands-on technical experience in a data science role with extensive experience in creating long-term data science strategy and executing through roadmap implementation.

Must also have: (I) 5 years of experience must include: a. 2 years of experience in building, leading, and managing a team of data scientists, data engineers and data analysts, b. 3 years of experience with Natural Language Processing techniques (including text wrangling, pre-processing, parsing, embedding, n-grams), and Machine Learning (including classifiers, clustering, time series, ANN, CNN, RNN, LSTM); (II) Demonstrated in depth experience: a. with Python and R and demonstrated comfort developing code in a team environment (including git, notebooks, and testing), b. with data modeling and data warehousing in SQL-based languages in a fast-paced business environment with large-scale and complex datasets, and c. with data visualization tools including Tableau, Spotfire, and Looker for full-stack data analysis, insight synthesis and presentation; (III) Demonstrated familiarity with the ipython notebook, Numpy, Pandas, Sklearn and NLTK; (IV) Strong proficiency with at least one common Deep Learning framework including TensorFlow, Keras, PyTorch, or MXNet; (V) Excellent communication, social and presentation skills with meticulous attention to detail; (VI) Track record of initiating and managing cross-functional and cross-organizational projects, building relationships with stakeholders, and influencing decision makers; (VII) Track record applying an analytical, creative and innovative approach to solving difficult problems; (VIII) Demonstrated ability to thrive in a dynamic environment where there can be degrees of ambiguity; (IX) Strong track record of communicating and partnering with senior stakeholders to deliver scalable global solutions; (X) Demonstrated expertise in: a. demand forecast using Time Series models such as SARIMAX, ETS, TBATS, GRU, or LSTM, b. classification models using Machine Learning/Deep Learning on highly imbalanced datasets, c. Natural Language Processing and Deep Learning models for language understanding tasks such as Named Entity Recognition, Text Matching, or Topic Modeling; and d. Extract, transform, load (ETL), Data Assessment, Data Mapping and Transformation, Master Data Management; and (XI) Track record of recruiting talent in analytics, data science and data engineer.

Apply online at https://jobs.lever.co/takeoff. An EOE.



Some of the ways we are addressing Covid-19:


While Covid-19 has posed its fair share of challenges, we have tackled these head on, while continuing to ensure that the health and safety of our employees and clients remain top priorities. We certainly believe that building a successful company starts with the people, and while the chance to meet and collaborate face to face in an office setting is vital to our growth and company culture, the health and safety of the Takeoff team is the most important right now. To that end, we are embracing a work remote first company policy, however the expectation is that you are based in the Greater Boston / MA area to ensure time zones are aligned with the rest of the Takeoff team based on the east coast.


Whether it be a Cultural Brunch & Learn, a Rocketberry Mini-Series showcasing some of our teams dynamic and hidden talents, or a weekly coffee chat to catch up with your fellow colleagues, we are finding creative ways to stay connected and engaged with each other during these challenging times.


Lastly along with our robust and competitive benefits package that we offer(above), we are excited to roll out two new benefits; a remote work allowance as well as a remote office setup reimbursement. These benefits will be effective immediately upon hire date geared towards ensuring that our employees are continuously set up for success while working remotely!


Equal Opportunity Employer


Our culture revolves around our core values of respect, initiative, collaboration, adaptability and diversity. As people, we value hard work, but we balance it with socializing as a team, respecting our time outside of work, and appreciating our coworkers unique walks of life.


Takeoff is an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. Learn more at www.takeoff.com. We believe that diversity is critical to the growth of our company; we foster an environment where everyone has a voice and views the Takeoff team as their second family.

Full-time

Employee Testimonials

Jake Williams
Jake Williams
Fulfillment Product Lead

The culture here is so unlike big companies. It’s warm and friendly. We eat lunch together every day. It really feels like family.

Jean Achorn
Jean Achorn
Communications Specialist

Everyone here really believes in what they do. We work hard, but we also know how to have fun!

William Odom
William Odom
Design & Continuous Improvement Lead - Fulfillment

My favorite thing about working at Takeoff is the collaborative environment. We're all part of the team.

Anastasiia Klimova
Anastasiia Klimova
QA Engineer

At the end of the day, Takeoff really cares about their employees. It's great to work at a place that appreciates each and every team member.

Geraldi Prenata
UX Intern

Last Friday, I completed my 13-week summer internship with Takeoff Technologies as a UX intern. I really enjoy working in such a warm, friendly, and collaborative environment. I learned about creating user personas, performing user research, testing, and interview for our fulfillment & supply chain apps. I learned how to conduct an effective competitive analysis and analogous research to gain insights on current trends of competitors and eGrocery market. I also learned how to analyze user behavior and engagement using different analytical tools, and implement the findings to further improve our apps usability and features. Last but not least, I would like to thank my manager Becky Carpenter and Laura Cody from the UX team for teaching me the principles of Lean UX, product design, and collaboration with other departments.