- Selecting features and building recommendation engines using machine learning techniques.
- Data pre-processing using state-of-the-art methods.
- Enriching the company's data from third-party sources when required.
- Enhancing data collection procedures to include information that is relevant for building analytical systems.
- Creating automated anomaly detection systems and constant tracking of the performance of the Recommendation Engine.
- Develop custom data models and algorithms to apply to data sets.
- Assess the effectiveness and accuracy of new data sources and data gathering techniques.
- Coordinate with various devs and businesses to implement models and monitor outcomes.
- Develop processes and tools to monitor and analyze model performance and data accuracy.
- Must have experience with working on Recommendation Systems. Must be well-versed with deep learning frameworks such as TensorFlow or Keras.
- Must be proficient in Python and other machine learning languages.
- Must possess the ability to approach a data science problem and find smart and relevant solutions.
- Deep understanding of data structures, data modeling and software architecture.
- Ability to conduct rigorous analysis of data and chart out clear take away(s) from Big Data sources.
- Must be proficient in Natural Language programming.
- Must have extensive knowledge of probability and statistical skills, model selectors, advanced regression techniques like AIC, BIC, HyperParameters, Content based and Collaborative Filtering methods, etc.
- Python packages such as Numpy, Scipy, Pandas, Sklearn, Matplotlib and Tensorflow/Keras.
- Experience with various messaging systems, such as Kafka or RabbitMQ will be considered a plus.
- Experience with Big Data ML toolkits, such as Mahout, SparkML, or H2O is preferred.
- Implementation including loading from disparate data sets, preprocessing using Hive and Pig will add huge value.
- Must be able to assess the scope of Big Data solutions and deliver on them.
- Should possess the ability to design solutions independently based on high-level architecture.
- Should co-ordinate the technical communication between the survey vendor/partner and internal systems.
- Must be capable of maintaining the production systems (Kafka, Hadoop, Cassandra, Elasticsearch).
- Collaborate with other development and research teams. Experience with building stream-processing systems, using solutions such as Storm or SparkStreaming.
- Experience with NoSQL databases, such as HBase, Cassandra, MongoDB.
- Experience with integration of data from multiple sources.
- Setting up and Management of Hadoop cluster, with all included services.
- Deploying the model into production, detecting anomalies, fine tuning HyperParameters, and cross validating as needed. Estimating resources, GPU requirements, analyzing cost of running a continuous. recommendation engine, ensuring stability of the model, performance, accuracy etc.
- Hands on experience with Machine Learning/Deep Learning algorithms such as Linear Regressions, Logistic Regression, Decision Tree, SVM, Random Forests, Bagging and Boosting, Recommendation systems, ANN, CNN & RNN etc.
- Experience with distributed data/computing tools: MapReduce, Hadoop, Hive, Spark, Flink, etc. Experience using web services: Redshift, S3, etc.
- Experience creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees etc.
- A Kaggle profile with a list of relevant projects is preferred.
- Good hold of data architectures, competitive coding challenges is preferred.
- Experience building data pipeline, knowledge of DevOps and application monitoring systems is preferred.
- 3+ years of experience in Spark, HBase, Hive, Sqoop, Oozie, Flume, Java, Pig, Python etc.
Other qualities we look for:
Build Collaborative partnerships: Must be able to build a powerful team profile to ensure you are recognized and respected as a strong leader. Should demonstrate a natural ability to build mutually beneficial partnerships with stakeholders at all levels, internally and externally.
Consulting Advisory Services: Should be able to provide expert knowledge and recommendations that will contribute to the growth of the business.
Result Oriented Work Ethic: Should display strong thought leadership and take responsibility for the teams performance, holding all stakeholders accountable as and when required.
Anticipate The Needs of the Industry: Must be able to predict or anticipate business issues or problems for which Gameopedia can provide solutions, and identify and evaluate their feasibility.
Build Talent: Should be able to promote and encourage a culture of continuous learning and growth across the team.
Agile and innovative: Must possess intellectual flexibility and strong lateral thinking abilities.
Purposeful and aligned: Must have the ability to set clear, tangible objectives which deliver against our strategy.
Coach: Must demonstrate the ability to coach, mentor, inspire and develop others while facilitating learning, growth, and engagement.
Intellectual curiosity: Must have an insatiable thirst for knowledge and be continuously motivated to understand our system better.
Experience and Education:
Experience: 5 to 10 years
Masters/B.Tech/M.Tech in Engineering, Applied Math, Statistics
- Competitive salary.
- Health insurance.
- Flexible working arrangements.
- Casual dress code.
- Collaboration friendly office.