A solid foundation in statistics, either demonstrated through academic study or work experience.
Experience with at least two programming languages and one general-purpose statistical package or programming library. The data science team mainly uses R, Scala, and Ruby, but that’s not set in stone, and we value the ability to learn new libraries and ecosystems.
Friendly and ready to work with others, both technical and non-technical. We don’t work in isolation and regularly interact with each other and members of other teams.
At least some familiarity with: Unix-like operating systems, SQL databases, and web application programming. Strong experience in any is a plus.
Other pluses: experience with distributed-computing ecosystems like Spark; experience with Amazon Web Services; experience teaching statistics or programming.
Smartling is seeking a Data scientist to join our engineering team. We are a small, tight-knit, dynamic group of engineers building and maintaining various smart systems that our customers rely on to maximize their value in using our platform. In this role, you will be responsible for tasks like identifying metrics and points of data to track and pre-processing data via Python.
Translate product and business objectives to data science problems and vice versa.
Define and report key performance metrics.
Develop methodologies in sampling, A/B testing, and survey design.
Apply statistical inference to draw rigorous conclusions from data.
Use a combination of exploratory analysis and data mining techniques to identify and interpret trends and anomalies.
Communicate results and make actionable recommendations to stakeholders in Product, Marketing, and Community.
The Data Science and Monetization team is responsible for tackling some of the company's most difficult problems and distilling its large volumes of data into relevant, actionable knowledge. Candidates must have a strong foundation of technical and quantitative skills and be focused on how insights can impact business results. While analytic rigor is a must, this is an applied research function where impact matters more than techniques utilized. Areas of focus range from business intelligence, predictive modeling, product testing, pricing strategy, financial modeling, self-service reporting automation, data architecture development, and marketing decision support.
You'll join a growing analytics team that drives Attune’s business model forward by solving some of the most complex analytical problems in the industry. You will partner with the actuarial, underwriting, claims, product, revenue and customer service functions within Attune to frequently test new hypotheses, implement learnings and create edge.
Leverage cutting-edge data science capabilities and technology to design products used to help healthcare clients plan, target, measure and optimize their marketing campaigns.
Contribute to the development of Crossix’s rapidly growing and market leading programmatic modeling solutions.
Help to discover and deliver innovative advanced analytics powered features and product offerings from prototype to massive scale.
Apply machine learning and advanced analytics techniques to large data sets of health and consumer data.
Explore and find meaning in extremely high volumes of data to extract actionable insights that will help drive business decisions; perform data query, data cleansing and experiment design.
You’ll be a member of our data science team with a focus on ads measurement. In this role, you will be a subject matter expert on every part of our ads measurement offering – conversion lift and experiments, synthetic controls, reach and frequency, brand lift, etc. In addition, you will be an expert in the processes and data that enable these solutions – understanding the role of identity and advocating for changes if needed, building ways to account for missing transaction data, correcting non-response bias, panel bias, and so on. Your day-to-day will be spent interfacing between our Product Management, Data Partnerships, and Data Engineering teams to help lead the development and improvement of our measurement solutions. In this role you may also serve as a technical lead, guiding projects and mentoring junior members of the team
· Responsible for full-cycle development of machine learning models from data collection and cleansing to feature engineering to model selection, prototyping and validation to A/B testing to deployment on managed cloud platforms to documentation and maintenance.
Develop data collection, forecasting, and reporting procedures that instantly highlight business opportunities, flag potential issues, and ease reporting to all business stakeholders.
Work with a global team on data science challenges related to online advertising.
In this position, you are a key stakeholder in the company’s data strategy and its implementation to generate value from data. You’ll be responsible for building and operationalizing data products (from data collection, cleaning, preprocessing, to training models and running them in production). The ideal candidate knows that data needs to marry math, and can communicate across the business to understand challenges and share solutions.
Customer Operations Data Scientists formulate the analytical frameworks and provide the technical rigor to measure the efficacy of, and shape the future for, Squarespace’s award-winning Customer Operations team. In close partnership with management, you’ll identify the fundamental questions we need to ask and have ownership over the data-driven means of addressing them.
Build innovative data products (i.e. real-time services, such as personalization and commerce graphing using Big Data platforms with real-time data ingestion and processing).
Execute descriptive analyses, ranging from identifying product opportunities to understanding user behavior.
Cultivate strong collaborative relationships with product, engineering, senior stakeholders.
Share your technical solutions and product ideas with the BCG Digital Ventures team through design review, pair programming, code reviews, and tech talks.
The Lead Data Scientist will be responsible for developing, executing, and overseeing the day-to-day management of the company’s data science team focused on personalization. Additionally, alongside the product and engineering teams, you will have a role in shaping the product. This is a great opportunity to build something from the ground up.