Data Scientist

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Apache Hadoop, Scala Programming, Machine learning techniques, Data science techniques, PyTorch, TensorFlow, MapReduce, R Programming

Job Description

The charter of Vistex’ data science team is to add more intelligence the go-to-market functionality that Vistex delivers to our customers. To achieve this, the data science team leverages expertise in data-driven science as well as acumen in business-to-business commerce. This data-driven science includes broad areas of data science, mathematics, statistics, econometrics, operations research, and computer science.

If you are an expert in at least one of these areas and are interested in becoming a well-rounded data scientist, then we are looking for you! This is your opportunity to build a portfolio of diverse projects in different industries proving that you can convert these advanced skills into impactful analytics with tangible results

Responsibilities:

• Execute independently analytical work such as data analysis, data mining, segmentation, modeling the relation between price levers and demand response, time series forecasting, and mathematical programming.
• Lead the execution of effective and efficient proof-of-concept and proof-of-value projects.
• Support the development, implementation and on-going use of analytic applications and models

About us: The Vistex platform helps businesses finally get control of all their different promotions, rebates, SPAs, discounts, and other incentives. With so many programs across so many partner relationships, it can be impossible to see where all the money is going, let alone how much difference it’s making to revenue. With Vistex, business leaders can see the numbers, see what really works, and see what to do next – so they can make sure every dollar they spend really is driving more growth, not just more costs. It’s why global enterprises ranging from Coca-Cola to Sony to Grainger rely on Vistex every day. Vistex | Now it all adds up.™

Qualifications

Behaviors

Preferred

• Dedicated: Devoted to a task or purpose with loyalty or integrity
• Innovative: Consistently introduces new ideas and demonstrates original thinking
• Detail Oriented: Capable of carrying out a given task with all details necessary to get the task done well

Motivations

Preferred

• Ability to Make an Impact: Inspired to perform well by the ability to contribute to the success of a project or the organization
• Goal Completion: Inspired to perform well by the completion of tasks

Education

Required

• Masters or better in Computer Science or related field.
• Masters or better in Engineering or related field.

Experience

Required

3 years: - min 3 years of practical experience in data analytics and a bachelor’s degree with a major in a quantitative science, such as (but not limited to) data science, mathematics, statistics, econometrics, operations research, and computer science.

a genuine interest in the business impact of the application of advanced analytics as well as a keen ability to work collaboratively across the organization, especially with Solution Delivery, Product Management, and Sales.

experience in using mathematical programming packages such as C-Plex, Coin-OR, OR-Tools, or Gurobi, programming languages such as C++, Python, C#, or Java, machine learning libraries, including PyTorch and TensorFlow, databases related skills, such as SQL, JSON, XML and big/distributed data such as Hadoop, HBase, and Hana.

• experience in simulation techniques, for example, discrete even modeling and agent-based modeling.
• practical knowledge in statistics and econometrics, including design of experiments, forecasting and time-series analysis, logistic regression, and Bayesian techniques.
• mathematical programming skills such as linear & integer programming, dynamic programming, and stochastic optimization.
• machine-learning techniques, such as classification, ensemble methods, deep learning, reinforcement learning, or natural language processing.
• knowledge of go-to-market processes, marketing measurement and channels of distribution.