Data Scientist

You will:

• Create highly scalable AWS micro-services utilizing cutting edge cloud technologies.
• Design and develop Big Data pipelines handling huge geospatial data.
• Bring clarity to large complex technical challenges.
• Collaborate with Engineering leadership to help drive technical strategy.
• Project scoping, planning and estimation.
• Mentor and coach team members at different levels of experience.
• Participate in peer code reviews and technical meetings.
• Cultivate a culture of engineering excellence.
• Seek, implement and adhere to standards, frameworks and best practices in the industry.
• Participate in on-call rotation.

You have:

• Bachelor’s/Master’s degree in computer science, computer engineering or relevant field.
• 5+ years of experience in software design, architecture and development.
• 5+ years of experience using object-oriented languages (Java, Python).
• Strong experience with Big Data technologies like Hadoop, Spark, Map Reduce, Kafka, etc.
• Strong experience in working with different AWS technologies.
• Excellent competencies in data structures & algorithms.

Nice to have:

• Proven track record of delivering large scale projects, and an ability to break down large tasks into smaller deliverable chunks
• Experience in developing high throughput low latency backend services
• Affinity to spatial data structures and algorithms.
• Familiarity with Postgres DB, Google Places or Mapbox APIs

Roles and Responsibilities

• Managing available resources such as hardware, data, and personnel so that deadlines are met.
• Analyzing the ML and Deep Learning algorithms that could be used to solve a given problem and ranking them by their success probabilities
• Exploring data to gain an understanding of it, then identifying differences in data distribution that could affect performance when deploying the model in the real world
• Defining validation framework and establish a process to ensure acceptable data quality criteria are met
• Supervising the data acquisition and partnership roadmaps to create stronger product for our customers.
• Defining feature engineering process to ensure usage of meaningful features given the business constraints which may vary by market
• Device self-learning strategies through analysis of errors from the models
• Understand business issues and context, devise a framework for solving unstructured problems and articulate clear and actionable solutions underpinned by analytics.
• Manage multiple projects simultaneously while demonstrating business leadership to collaborate & coordinate with different functions to deliver the solutions in a timely, efficient and effective manner.
• Manage project resources optimally to deliver projects on time; drive innovation using residual resources to create strong solution pipeline; provide direction, coaching & training, feedbacks to project team members to enhance performance, support development and encourage value aligned behaviour of the project team members; Provide inputs for periodic performance appraisal of project team members.

Preferred Technical & Professional expertise

• Undergraduate Degree in Computer Science / Engineering / Mathematics / Statistics / economics or other quantitative fields
• At least 2+ years of experience of managing Data Science projects with specializations in Machine Learning
• In-depth knowledge of cloud analytics tools.
• Able to drive Python Code optimization; ability review codes and provide inputs to improve the quality of codes
• Ability to evaluate hardware selection for running ML models for optimal performance
• Up to date with Python libraries and versions for machine learning; Extensive hands-on experience with Regressors; Experience working with data pipelines.
• Deep knowledge of math, probability, statistics and algorithms; Working knowledge of Supervised Learning, Adversarial Learning and Unsupervised learning
• Deep analytical thinking with excellent problem-solving abilities
• Strong verbal and written communication skills with a proven ability to work with all levels of management; effective interpersonal and influencing skills.
• Ability to manage a project team through effectively allocation of tasks, anticipating risks and setting realistic timelines for managing the expectations of key stakeholders
• Strong organizational skills and an ability to balance and handle multiple concurrent tasks and/or issues simultaneously.
• Ensure that the project team understand and abide by compliance framework for policies, data, systems etc. as per group, region and local standards

• Participate in full machine learning Lifecycle including data collection, cleaning, preprocessing to training models, and deploying them to Production.
• Discover data sources, get access to them, ingest them, clean them up, and make them “machine learning ready”. 
• Work with data scientists to create and refine features from the underlying data and build pipelines to train and deploy models. 
• Partner with data scientists to understand and implement machine learning algorithms. 
• Support A/B tests, gather data, perform analysis, draw conclusions on the impact of your models. 
• Work cross-functionally with product managers, data scientists, and product engineers, and communicate results to peers and leaders. 
• Mentor junior team members 

Who we have in mind:

• Graduate in Computer Science or related field, or equivalent practical experience. 
• 4+ years of experience in software engineering with 2+ years of direct experience in the machine learning field.
• Proficiency with SQL,  Python, Spark, and basic libraries such as Scikit-learn, NumPy, Pandas.
• Familiarity with deep learning frameworks such as TensorFlow or Keras
• Experience with Computer Vision (OpenCV),  NLP frameworks (NLTK, SpaCY, BERT).
• Basic knowledge of machine learning techniques (i.e. classification, regression, and clustering). 
• Understand machine learning principles (training, validation, etc.) 
• Strong hands-on knowledge of data query and data processing tools (i.e. SQL) 
• Software engineering fundamentals: version control systems (i.e. Git, Github) and workflows, and ability to write production-ready code. 
• Experience deploying highly scalable software supporting millions or more users 
• Experience building applications on cloud  (AWS or Azure) 
• Experience working in scrum teams with Agile tools like JIRA
• Strong oral and written communication skills. Ability to explain complex concepts and technical material to non-technical users

• You'd have to set up your own shop, work with design customers to find generalizable use cases, and build them out.
• Ability to collaborate with cross-functional teams to build and ship new features
• At least 2-5 years of experience
• Predictive Analytics – Machine Learning Algorithms, Logistics & Linear Regression, Decision Tree, Clustering. 
• Exploratory Data Analysis – Data Preparation, Data Exploration, and Data Visualization. 
• Analytics Tools – R, Python, SQL, Power BI, MS Excel.

• Measure the sales effectiveness efforts using data science/app/digital nudges.
• Should be able to work on the clickstream data
• Should be well versed and willing to work hands-on various Machine Learning techniques

Skills

• Ability to lead a team of 5-6 members.
• Ability to work with large data sets and present conclusions to key stakeholders.
• Develop a clear understanding of the client’s business issue to inform the best approach to the problem.
• Root-cause analysis
• Define data requirements for creating a model and understand the business problem
• Clean, aggregate, analyze, interpret data and carry out quality analysis of it
• Set up data for predictive/prescriptive analysis
• Development of AI/ML models or statistical/econometric models.
• Working along with the team members
• Looking for insight and creating a presentation to demonstrate these insights
• Supporting development and maintenance of proprietary marketing techniques and other knowledge development projects.