Senior Data Scientist

About antuit.ai

Antuit.ai is the leader in AI-powered SaaS solutions for Demand Forecasting & Planning, Merchandising and Pricing. We have the industry’s first solution portfolio – powered by Artificial Intelligence and Machine Learning – that can help you digitally transform your Forecasting, Assortment, Pricing, and Personalization solutions. World-class retailers and consumer goods manufacturers leverage antuit.ai solutions, at scale, to drive outsized business results globally with higher sales, margin and sell-through.

Antuit.ai’s executives, comprised of industry leaders from McKinsey, Accenture, IBM, and SAS, and our team of Ph.Ds., data scientists, technologists, and domain experts, are passionate about delivering real value to our clients. Antuit.ai is funded by Goldman Sachs and Zodius Capital.

The Role:

Antuit.ai is interested in hiring a Principal Data Scientist, this person will facilitate standing up standardization and automation ecosystem for ML product delivery, he will also actively participate in managing implementation, design and tuning of product to meet business needs.

Responsibilities:

Responsibilities includes, but are not limited to the following:

• Manage and provides technical expertise to the delivery team. This includes recommendation of solution alternatives, identification of risks and managing business expectations.
• Design, build reliable and scalable automated processes for large scale machine learning.
• Use engineering expertise to help design solutions to novel problems in software development, data engineering, and machine learning. 
• Collaborate with Business, Technology and Product teams to stand-up MLOps process.
• Apply your experience in making intelligent, forward-thinking, technical decisions to delivery ML ecosystem, including implementing new standards, architecture design, and workflows tools.
• Deep dive into complex algorithmic and product issues in production
• Own metrics and reporting for delivery team. 
• Set a clear vision for the team members and working cohesively to attain it.
• Mentor and coach team members

Qualifications and Skills:

Requirements

• Engineering degree in any stream
• Has at least 7 years of prior experience in building ML driven products/solutions
• Excellent programming skills in any one of the language C++ or Python or Java.
• Hands on experience on open source libraries and frameworks- Tensorflow,Pytorch, MLFlow, KubeFlow, etc.
• Developed and productized large-scale models/algorithms in prior experience
• Can drive fast prototypes/proof of concept in evaluating various technology, frameworks/performance benchmarks.
• Familiar with software development practices/pipelines (DevOps- Kubernetes, docker containers, CI/CD tools).
• Good verbal, written and presentation skills.
• Ability to learn new skills and technologies.
• 3+ years working with retail or CPG preferred.
• Experience in forecasting and optimization problems, particularly in the CPG / Retail industry preferred.

Information Security Responsibilities

• Understand and adhere to Information Security policies, guidelines and procedure, practice them for protection of organizational data and Information System.
• Take part in Information Security training and act accordingly while handling information.
• Report all suspected security and policy breach to Infosec team or appropriate authority (CISO).

EEOC

• A Natural Language Processing (NLP) expert with strong computer science fundamentals and experience in working with deep learning frameworks. You will be working at the cutting edge of NLP and Machine Learning.

Roles and Responsibilities

• Work as part of a distributed team to research, build and deploy Machine Learning models for NLP.
• Mentor and coach other team members
• Evaluate the performance of NLP models and ideate on how they can be improved
• Support internal and external NLP-facing APIs
• Keep up to date on current research around NLP, Machine Learning and Deep Learning

Mandatory Requirements

• Any graduation with at least 2 years of demonstrated experience as a Data Scientist.

Behavioral Skills

Strong analytical and problem-solving capabilities.

• Proven ability to multi-task and deliver results within tight time frames
• Must have strong verbal and written communication skills
• Strong listening skills and eagerness to learn
• Strong attention to detail and the ability to work efficiently in a team as well as individually

Technical Skills

Hands-on experience with

• NLP
• Deep Learning
• Machine Learning
• Python
• Bert

Preferred Requirements

• Experience in Computer Vision is preferred

Job brief

We are looking for a Lead Data Scientist to lead a technical team and help us gain

useful insight out of raw data.

Lead Data Scientist responsibilities include managing the data science team, planning

projects and building analytics models. You should have a strong problem-solving ability

and a knack for statistical analysis. If you’re also able to align our data products with our

business goals, we’d like to meet you.

Your ultimate goal will be to help improve our products and business decisions by

making the most out of our data.

Responsibilities

● Conceive, plan and prioritize data projects

● Ensure data quality and integrity

● Interpret and analyze data problems

● Build analytic systems and predictive models

● Align data projects with organizational goals

● Lead data mining and collection procedures

● Test performance of data-driven products

● Visualize data and create reports

● Build and manage a team of data scientists and data engineers

Requirements

● Proven experience as a Data Scientist or similar role

● Solid understanding of machine learning

● Knowledge of data management and visualization techniques

● A knack for statistical analysis and predictive modeling

● Good knowledge of R, Python and MATLAB

● Experience with SQL and NoSQL databases

● Strong organizational and leadership skills

● Excellent communication skills

● A business mindset

● Degree in Computer Science, Data Science, Mathematics or similar field

● Familiar with emerging/cutting edge, open source, data science/machine learning

libraries/big data platforms

• Partnering with internal business owners (product, marketing, edit, etc.) to understand needs and develop custom analysis to optimize for user engagement and retention
• Good understanding of the underlying business and workings of cross functional teams for successful execution
• Design and develop analyses based on business requirement needs and challenges.
• Leveraging statistical analysis on consumer research and data mining projects, including segmentation, clustering, factor analysis, multivariate regression, predictive modeling, etc.
• Providing statistical analysis on custom research projects and consult on A/B testing and other statistical analysis as needed. Other reports and custom analysis as required.
• Identify and use appropriate investigative and analytical technologies to interpret and verify results.
• Apply and learn a wide variety of tools and languages to achieve results
• Use best practices to develop statistical and/ or machine learning techniques to build models that address business needs.

• 2 - 4 years  of relevant experience in Data science.
• Preferred education: Bachelor's degree in a technical field or equivalent experience.
• Experience in advanced analytics, model building, statistical modeling, optimization, and machine learning algorithms.
• Machine Learning Algorithms: Crystal clear understanding, coding, implementation, error analysis, model tuning knowledge on Linear Regression, Logistic Regression, SVM, shallow Neural Networks, clustering, Decision Trees, Random forest, XGBoost, Recommender Systems, ARIMA and Anomaly Detection. Feature selection, hyper parameters tuning, model selection and error analysis, boosting and ensemble methods.
• Strong with programming languages like Python and data processing using SQL or equivalent and ability to experiment with newer open source tools.
• Experience in normalizing data to ensure it is homogeneous and consistently formatted to enable sorting, query and analysis.
• Experience designing, developing, implementing and maintaining a database and programs to manage data analysis efforts.
• Experience with big data and cloud computing viz. Spark, Hadoop (MapReduce, PIG, HIVE).
• Experience in risk and credit score domains preferred.

Job Summary

As a Data Science Lead, you will manage multiple consulting projects of varying complexity and ensure on-time and on-budget delivery for clients. You will lead a team of data scientists and collaborate across cross-functional groups, while contributing to new business development, supporting strategic business decisions and maintaining & strengthening client base

1. Work with team to define business requirements, come up with analytical solution and deliver the solution with specific focus on Big Picture to drive robustness of the solution
2. Work with teams of smart collaborators. Be responsible for their appraisals and career development.
3. Participate and lead executive presentations with client leadership stakeholders.
4. Be part of an inclusive and open environment. A culture where making mistakes and learning from them is part of life
5. See how your work contributes to building an organization and be able to drive Org level initiatives that will challenge and grow your capabilities.

​​​​​​Role & Responsibilities

1. Serve as expert in Data Science, build framework to develop Production level DS/AI models.
2. Apply AI research and ML models to accelerate business innovation and solve impactful business problems for our clients.
3. Lead multiple teams across clients ensuring quality and timely outcomes on all projects.
4. Lead and manage the onsite-offshore relation, at the same time adding value to the client.
5. Partner with business and technical stakeholders to translate challenging business problems into state-of-the-art data science solutions.
6. Build a winning team focused on client success. Help team members build lasting career in data science and create a constant learning/development environment.
7. Present results, insights, and recommendations to senior management with an emphasis on the business impact.
8. Build engaging rapport with client leadership through relevant conversations and genuine business recommendations that impact the growth and profitability of the organization.
9. Lead or contribute to org level initiatives to build the Tredence of tomorrow.

Qualification & Experience

1. Bachelor's /Master's /PhD degree in a quantitative field (CS, Machine learning, Mathematics, Statistics, Data Science) or equivalent experience.
2. 6-10+ years of experience in data science, building hands-on ML models
3. Expertise in ML – Regression, Classification, Clustering, Time Series Modeling, Graph Network, Recommender System, Bayesian modeling, Deep learning, Computer Vision, NLP/NLU, Reinforcement learning, Federated Learning, Meta Learning.
4. Proficient in some or all of the following techniques: Linear & Logistic Regression, Decision Trees, Random Forests, K-Nearest Neighbors, Support Vector Machines ANOVA , Principal Component Analysis, Gradient Boosted Trees, ANN, CNN, RNN, Transformers.
5. Knowledge of programming languages SQL, Python/ R, Spark.
6. Expertise in ML frameworks and libraries (TensorFlow, Keras, PyTorch).
7. Experience with cloud computing services (AWS, GCP or Azure)
8. Expert in Statistical Modelling & Algorithms E.g. Hypothesis testing, Sample size estimation, A/B testing
9. Knowledge in Mathematical programming – Linear Programming, Mixed Integer Programming etc , Stochastic Modelling – Markov chains, Monte Carlo, Stochastic Simulation, Queuing Models.
10. Experience with Optimization Solvers (Gurobi, Cplex) and Algebraic programming Languages(PulP)
11. Knowledge in GPU code optimization, Spark MLlib Optimization.
12. Familiarity to deploy and monitor ML models in production, delivering data products to end-users.
13. Experience with ML CI/CD pipelines.

• 💰  Early-stage, ed-tech, funded, growing, growing fast.
• 🎯  Mission Driven: Make Indonesia competitive on a global scale.
• 🥅  Build the best educational content and technology to advance STEM education 
• 🥇  Students-First approach

• ❤️  Love what we do
• 🎮  Committed to making learning fun, accessible, and safe 
• 🤝  Teams are better. We value ownership, responsibility, transparency
• 🌏  Global, diverse backgrounds. Been there, done that.

• CoLearn has grown so much, and you’ve been an important part of the growth. You solved hard problems that many didn’t know existed.
• You’ve led the data science function and laid out the roadmap, implemented best practices, and grown the team. You’ve executed mission-critical projects. Congratulations!
• You’re exploring what Data Science can do for the students, parents, teachers, educators.
• You’ve been speaking at Data Science conferences about the image recognition system we built from scratch. You casually threw in the semantic search engine on slide 77.
• The engineering and product teams are your friends. The teams take cross-functional collaboration, testing, and modeling for granted. It’s their second nature.
• You have an encyclopedic knowledge of CoLearn’s data structures and metrics, and you’ve often provided key ideas for the product.

• Highly-skilled and experienced Data Scientist and leader
• You are interested in creating next-gen data-powered education tech products. 
• You’ve worked in a Data Science role before where you took a data product to market
• You are comfortable working with unknowns, evaluating the data, and applying scientific techniques to business problems and products
• You’ve built platforms and systems from scratch
• You have a track record of developing and deploying data-science models to production

• End-to-end AI/ML systems in the cloud, including data processing, feature engineering, and tuning of ML models in training and production (MLOps) — with both structured and unstructured data.
• Deep Learning and Computer Vision models, ideally in a production environment
• Hands-on Python/SQL, scikit-learn, Keras, PyTorch, Tensorflow, MXnet, etc. 
• Experience in Scala/Java/Go/C/C++ is a plus plus
• Airflow/Luigi/Oozie and the likes
• Familiarity with cloud deployment strategies (AWS/GCP) to deploy at scale

• B.S./B.E./M.S./PhD in a quantitative field such as Computer Science, Engineering, Math, Statistics or equivalent years of experience
• 10+ years of experience in data science, algorithmic engineering, and machine learning. Preferably solved problems from scratch to scale
• Experience in hiring, managing highly-performant teams, and mentoring data science, data engineering, and analytics teams 
• Experience developing a data science strategy, building the roadmap, and leading the execution
• Track record of recruiting talent in analytics and data science

• You’ve won algorithm and machine learning competitions such as ACM and Kaggle
• You have research publications and citations in top tier journals 
• You have a portfolio of side projects and can show it to us